MINISTRY OF AGRICULTURE AND COOPERATIVES

DEPARTMENT OF AGRICULTURE

TECHNICAL SERVICES BRANCH

COPPERBELT PROVINCE

CENTRE FOR DEVELOPMENT OF ADVANCED APPLIED COMPUTING

(CDAC), INDIA

B-30, Institutional Area, Sector-62, Noida- 201307 (U.P.)

TRAINING REPORT SUBMITED BY CHARLES BWALYA CHISANGA

Specialized Programme on Application Development using GIS & Remote

Sensing

Date 17th January to 11

th March 2011

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Table of Contents

Introduction..................................................................................................................................... 1

Education at CDAC, NOIDA ..................................................................................................... 1 Training Methodology .................................................................................................................... 1

Training Programme Objectives: ................................................................................................ 1 Software used during the training programme................................................................................ 1

Lectures................................................................................................................................... 2 Books and literature used for the training programme ................................................................... 2 Week 1: 17th -21st January 2011 .................................................................................................... 3

Lecture: Nimesh Dagur............................................................................................................... 3 AutoCAD Map........................................................................................................................ 3 Exercise/Practical.................................................................................................................... 3

Lecture: Dr. Shalini Singh........................................................................................................... 5 Introduction to GIS ................................................................................................................. 5

Lecture: Dr. Shalini Singh........................................................................................................... 6 Geographic Information System (GIS)................................................................................... 6

Week 2: 24th – 28th January 2011.................................................................................................11

Lecture: Dr. Shalini Singh..........................................................................................................11 ArcGIS ...................................................................................................................................11 Exercise/Practical...................................................................................................................11

Lecture: Dr Shalini Singh ......................................................................................................... 21 Exploring GIS concepts ........................................................................................................ 21 Exercise/Practical.................................................................................................................. 21

Lecture: Vinay Shankar Prasad Sinha....................................................................................... 27 Application of GIS in Watershed Analysis using ArcMap, ArcCatalog, ArcToolbar ........... 27 Geo-statistical Analysis, Conceptual model, and Practical Exercise .................................... 28 Exercise/Practical.................................................................................................................. 29 GIS DATA MODELS............................................................................................................ 32

Week 3: 31st January – 4th February 2011................................................................................... 34

Lecturer: Nimesh Dugar ........................................................................................................... 35 MapInfo................................................................................................................................. 35 Exercise/Practical.................................................................................................................. 35

Lecturer: Dr. Shalini Singh ....................................................................................................... 36 Remote Sensing and Data Collection ................................................................................... 36 Digital image Processing ...................................................................................................... 36 Digital Numbers.................................................................................................................... 36 Exercise/Practical.................................................................................................................. 36

Lecture: Shailendra Suman ....................................................................................................... 36 Software Project Management.............................................................................................. 36

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Software Development Life Cycle (SDLC) - SDLC Model................................................. 36 Lecture: Shailendra Suman ....................................................................................................... 38

Global Positioning System (GPS)......................................................................................... 38 Exercise/Practical.................................................................................................................. 38

Lecture: Shailendra Suman ....................................................................................................... 41 Principles of Remote Sensing (RS)....................................................................................... 41

Lecture: Dr. Shalini Singh......................................................................................................... 47 ERDAS IMAGINE ............................................................................................................... 47 Exercise/Practical.................................................................................................................. 47

Week 4: 7th – 11th February 2011 ................................................................................................ 47

Lecture: Shailendra Suman ....................................................................................................... 47 Space Segment Consideration (continued from week 3)...................................................... 47 Thermal Infrared Remote Sensing (continued from week 3) ............................................... 47 Active microwave (RADAR) ............................................................................................... 47

Lecture: Dr. Shalini Singh......................................................................................................... 49 ArcGIS .................................................................................................................................. 49 Introduction to Image Interpretation..................................................................................... 49 Digital Image Processing ...................................................................................................... 49 Digital Image Enhancement.................................................................................................. 49 Digital Image Classification ................................................................................................. 49 ERDAS Imagine ................................................................................................................... 49 Practicals on Image to image registration, Re-sampling nearest neighbor, striping and banding, Atmospheric correction, Classification, Image manipulation, Spectral Enhancement, Radiometric Correction, Modeler using ERDAS.......................................... 49 Remote Sensing and Data Collection ................................................................................... 50

Lecture: Dr. Shalini Singh......................................................................................................... 50 Digital image Processing and Classification......................................................................... 50 Linear Stretching................................................................................................................... 50 Change Detection.................................................................................................................. 50 Exercise/Practical.................................................................................................................. 50 Principal Component Analysis (PCA) .................................................................................. 50 Exercise/Practical.................................................................................................................. 50

Week 5: 14th – 19th February 2011.............................................................................................. 50

Lecture: Dr. Shalini Singh......................................................................................................... 50 Digital Image classification .................................................................................................. 50 Exercise/Practical.................................................................................................................. 50 GIS Modeling, ArcGIS3.3 and ArcGIS, Arctoolbox and ArcCatalog .................................. 53 Exercise/Practical.................................................................................................................. 53

Lecture: Nimesh Dagur............................................................................................................. 55 MapInfo................................................................................................................................. 55 Exercise and practical ........................................................................................................... 55

Week 6: 21st – 25th February 2011 .............................................................................................. 58 Lecture: Nimesh Dagur............................................................................................................. 58

Application GIS - RDBMS (SQL) – Oracle 9i ..................................................................... 58

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Introduction to Programming using Visual Studio 2005 ...................................................... 59 Exercise/Practical.................................................................................................................. 59

Week 7: 28th February – 5th March 2011 .................................................................................... 60

Lecture: Nimesh Dagur............................................................................................................. 60 Loop, Object Oriented Concepts........................................................................................... 60 Exercise/Practical.................................................................................................................. 60 Accessing Databases............................................................................................................. 60

Week 8: 7th – 11th March 2011 .................................................................................................... 61

Lecturer: Amjad Khan............................................................................................................... 61 Developing Application for Web Based GIS (continuation from week 7) ........................... 61 MapGuide and WebGIS ........................................................................................................ 61 Exercise/Practical.................................................................................................................. 61

Lecture: Amjad Khan................................................................................................................ 61 MapGuide and WebGIS ........................................................................................................ 61 Exercise/Practical.................................................................................................................. 61 Use of MapObjects and Microsoft Visual Studio .NET to build a simple mapping application using the Visual Basic (VB) language................................................................ 62 Exercise/Practical.................................................................................................................. 62

Industrial visit ............................................................................................................................... 63

RAMTech Cooperation......................................................................................................... 63 MapMyIndia ......................................................................................................................... 63

Conclusion .................................................................................................................................... 64 APPENDICES ................................................................................................................................. i Appendix 1: Course layout .............................................................................................................. i Appendix 2: list of Participants...................................................................................................... iii

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Introduction

Education at CDAC, NOIDA

Centre for Development of Advanced Computing (C-DAC) is a national initiative of the Government. of India, Ministry of Communication and IT to mobilize human and technical resources in order to attain technological advancement in the ever-evolving arena of Information Technology for the benefit of masses. C-DAC is a scientific society and one of the premier research institute of DIT, MCIT and has successfully integrated its computer education and training activities in Hi-tech areas with Research & Development in the area of Information Technology like Embedded Systems, Broadband, Multilingual technologies, GIS based Solutions, Digital library, Health care, eGovernance etc. CDAC has also established collaboration alliance with global technology leaders like Microsoft, IBM, Compaq and Oracle. It professes the policy of establishing the balance between research and teaching for higher education The training programmes conducted for international participants at C-DAC Noida are sponsored by the Govt. of India under the ITEC and SCAAP programmes. The allowance admissible to the participants includes the cost of air passage, free tuition, living allowance and lodging as per availability of accommodation.

Training Methodology

C-DAC adopts professional approach in imparting training to the participants wherein tentatively 50% time is devoted to lectures and same amount of time is devoted to labs to help participants to have a better understanding of concepts learnt in theory sessions. State-of-the-art infrastructure, well equipped library, experienced and qualified faculties are few of the things that make learning at CDAC a memorable experience. Besides classroom training, programmes such as expert sessions, visit to industries, cultural visits to historical monuments are conducted as a part of the training. The Historical sites of interest visited included Tajma hall (Agra), Red Fort, Baha’i Faith Temple, Botanical Garden.

Training Programme Objectives:

•••• To understand the GIS & Remote Sensing concepts; •••• To understand information relating to integration of GIS, Remote Sensing and

Application software development; and •••• To understand about Development of GIS Applications using Client/Server Architecture.

Software used during the training programme

• AutCAD Map

• MapInfo 9.1

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• ArcView3.3

• ArcGIS9.1

• ERDAS9.1

• ORACLE 9i

• Visual Basic 2008

• Map Objects

• MapWindowGIS

• MapGuide Studio

• MapGuide Maestro 2.1.4 & MapGuideOpenSource-2.1.0.4283-Final

Lectures Course Name

Amjad Khan Application Development for Web Based GIS (MapWindowGIS), MapGuide and WebGIS, MapGuide Studio

Dr. Shalini Singh Remote Sensing, DIP using ERDAS Nimesh Dagur AutoCAD Map, MapInfo, Visual Basic dot Net, MapObjects, SQL,

Introduction to Programming Nishant Sinha Remote Sensing (Principal Component Analysis) R. Kumar Remote Sensing: Active microwave (RADAR) Shailendera Suman Remote Sensing, System Development Life Cycle (SDLC) Vinay Prasad Sinha GIS Modeling

Books and literature used for the training programme

1. Bayross Ivan (2009), SQL, Pl/SQL The programming language of Oracle, 4th Revised Edition, BPB Publishing, New Delhi

2. Concepts on Geographic Information System 3. ERDAS Image Reference Manual 4. Heywood I, Cornelius S. and Carver S. (2009), An Introduction to Geographical Information

Systems 3rd Edition, Published by Dorling Kindersley, India Pvt Ltd 5. Lillesand T. M., Kiefer R. W., and Chipman J. W. (2004), Remote Sensing and image

Interpretation, Fifth Edition, Wiley Student Edition, John Wiley & Sons 6. Newsome B. and Willis T. (2008), Beginning Microsoft Visual Basic 2008, Wiley India Pvt

Ltd 7. Wilpen L. Gorr and Kristen S. Kurland, 2004, Learning and using Geographical Information

Systems; Cengage learning India Private Ltd, New Delhi 8. CD from CDAC

List of participants (see Appendix 2)

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Week 1: 17th -21st January 2011

Lecture: Nimesh Dagur

AutoCAD Map Exercise/Practical

AutoCAD Map

Key terms

• Map: a flat representation of a globe

• Cartography - the art and science of mapmaking

• Projection: The system used to transfer locations from Earth’s surface to a flat map.

• Scale: The relationship between the size of an object on a map and the actual size of the same feature on Earth’s surface.

• Map scale determines the size and shape of features

Map Scale

• Map scale is an important but often misunderstood concept in cartography. To represent a portion of the earth’s surface on a map, the area must be reduced. The extent of this reduction is expressed as a ratio called map scale. Map scale is the ratio of map distance to ground distance.

• For example, if you draw a 4.8-km road as a 20-cm line on your map, the following statements would describe the map scale:

• 20 cm : 4.8 km, 20 cm : 480,000 cm, 1 cm : 24,000 cm, 1 : 24,000

• The latter is known as a representative fraction (RF) because the values on either side of the colon represent the proportion between distance on the map and distance on the ground; that is, “1:24,000” means “1 map inch represents 24,000 ground inches”, “1 map meter represents 24,000 ground meters”, or “1 map centimeter represents 24,000 ground centimeters”, and so on.

• Map scale can be expressed in several different manners: as a fraction (1:24,000), as a verbal statement (one centimeter equals one kilometer), or as a bar.

• Map scale indicates how much a given distance was reduced to be represented on a map. For maps with the same paper size, features on a small-scale map (1:1,000,000) look smaller than those of a large-scale map (1:1,200). In other words, a dime-sized lake on a large scale map (l: 1,200) would be less than the size of the period at the end of this sentence on a small-scale map (1:1,000,000).

• In general, small-scale maps depict large ground areas, but they have low spatial resolution, showing little detail. On the other hand, large-scale maps depict small ground areas but have high spatial resolution, showing many details. The features on large-scale maps more closely represent real-world features because the extent of reduction is lower than that of a small-scale map. As map scale decreases, features must be smoothed and simplified or not shown at all. For example, at a scale of 1:63,360 (in which 1 inch = 1 mile), it is difficult to represent area features smaller than 1/8th of a mile long or wide because they will be 1/8th of an inch long or wide on a map.

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AutCAD Map

• AutoCAD Map is the leading engineering solution for creating and managing spatial data.

• AutoCAD Map bridges the gap between Computer Aided Design

• (CAD) and Geographic Information Systems (GIS).

• AutoCAD Map provides direct access to the leading data formats used in design and GIS.

• Use AutoCAD tools to maintain a broad variety of geospatial information.

Purpose of a map

A map is a representation of the features that occur on the Earth. Maps allow us to accomplish a number of things, such as:

• Visualize Information

• Obtain the spatial orientation and relationships of our data

• Present results of analysis AutoCAD uses file extension *.dwg, *.dgn and *.dxf. It can also display shapefiles. Vector based shapefiles are comprised of a combination of four layer types: point, line, polygon and annotation. A shapefile is a digital vector storage format for storing geometric location and associated attribute information. This format lacks the capacity to store topological information. Shapefiles are simple because they store primitive geometrical data types of points, lines, and polygons. These primitives are of limited use without any attributes to specify what they represent. Therefore, a table of records will store properties/attributes for each primitive shape in the shapefile. Shapes (points/lines/polygons) together with data attributes can create infinitely many representations about geographical data. Representation provides the ability for powerful and accurate computations. While the term "shapefile" is quite common, a "shapefile" is actually a set of several files. Three individual files are mandatory to store the core data that comprises a shapefile: ".shp", ".shx", ".dbf", and other extensions on a common prefix name (e.g., "lakes.*"). The actual shapefile relates specifically to files with the ".shp" extension, but alone is incomplete for distribution, as the other supporting files are required. There are a further eight optional files which store primarily index data to improve performance. Each individual file should conform to the MS DOS 8.3 filename convention (8 character filename prefix, period, 3 character filename suffix such as shapefil.shp) in order to be compatible with past applications that handle shapefiles, though many recent software applications accept files with longer names. For this same reason, all files should be located in the same folder.

Mandatory files:

• .shp — shape format; the feature geometry itself

• .shx — shape index format; a positional index of the feature geometry to allow seeking forwards and backwards quickly

• .dbf — attribute format; columnar attributes for each shape, in dBase IV format

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Optional files:

• .prj — projection format; the coordinate system and projection information, a plain text file describing the projection using well-known text format

• .sbn and .sbx — a spatial index of the features

• .fbn and .fbx — a spatial index of the features for shapefiles that are read-only

• .ain and .aih — an attribute index of the active fields in a table or a theme's attribute table

• .ixs — a geocoding index for read-write shapefiles

• .mxs — a geocoding index for read-write shapefiles (ODB format)

• .atx — an attribute index for the .dbf file in the form of shapefile.columnname.atx

• .shp.xml — metadata in XML format

• .cpg — used to specify the code page (only for.dbf) for identifying the character encoding to be used

In each of the .shp, .shx, and .dbf files, the shapes in each file correspond to each other in sequence. That is, the first record in the .shp file corresponds to the first record in the .shx and .dbf files, and so on. The .shp and .shx files have various fields with different endianness, so as an implementor of the file formats you must be very careful to respect the endianness of each field and treat it properly. Shapefiles deal with coordinates in terms of X and Y, although they are often storing longitude and latitude, respectively. While working with the X and Y terms, be sure to respect the order of the terms (longitude is stored in X, latitude in Y).

Shapefile shape format (.shp)

The main file (.shp) contains the primary geographic reference data in the shapefile. The file consists of a single fixed length header followed by one or more variable length records. Each of the variable length records includes a record header component and a record contents component. A detailed description of the file format is given in the Esri Shapefile Technical Description. This format should not be confused with the AutoCAD shape font source format, which shares the .shp extension.

Lecture: Dr. Shalini Singh

Introduction to GIS

Geography and Technology

• Geography affects us in many ways:

– Our natural environment – Our human environment

• Geography has become a high tech discipline

– Earth Observation – Global Positioning Systems (GPS) – Geographic Information Systems (GIS)

Earth Observation • SPOT

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• Landsat TM • RadarSAT • NOAA • ERS

Global Positioning Systems

• GPS is a revolutionary navigation system – 24 satellites orbiting the earth – Provide location within metres or less anywhere on the globe. – Now available in many cars as an option

Geographic Information System (GIS)

• A Method of Organizing Data – Geographic Data (Maps) – Descriptive Data (Databases) – Images

• A Method of Distributing Data • A Method of Analyzing Data • A Method of Visualizing Data

GIS – Describing Our World

We can describe any element of our world in two ways: Location Information: Where is it? ((51°N, 112°W)

Attribute Information:What is it? ((Species: Oak; Height: 15m; Age: 75 Yrs; Condition: Good)

GIS - Links Datasets

GIS software links the location data and the attribute data

GIS - Analysis

GIS software can answer questions about our world: Spatial Questions: What provinces border Saskatchewan?

Attribute Questions: What provinces have more than 1.5 million people?

How GIS works

• In a GIS, different types of information are represented as separate map layers

• Each layer is linked to descriptive information

• Layers are combined to make a map

Lecture: Dr. Shalini Singh

Geographic Information System (GIS)

Definitions

• A system for capturing, storing, checking, manipulating, analyzing and displaying data which are spatially referenced to the Earth. • Any manual or computer based set of procedures used to store and manipulate geographically

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referenced data (Runoff, 1989) • A database system in which most of the data are spatially indexed, and upon which a set of procedures operated in order to answer queries about spatial entities in the database. (Smith,

1987) A geographic information system (GIS) is a collection of hardware, software, geographic data, and personnel designed to create, store, edit, manipulate, analyze and display geographically referenced information.

How does a GIS work?

• GIS stores information as a collection of thematic layers • Thematic layers are linked together by geography

• Explicit geographic reference (latitude and longitude) Implicit reference (address, postal code, FIPS code, census tract, road name)

• GIS can create explicit geographic features (e.g., customer) from implicit references like customer address

• Geographic features (points, lines, polygons) used for visualization and analysis

• GIS is a computerized decision support system that integrates geographic data, attribute data and other spatially referenced data. GIS is used to capture, store, retrieve, analyze, and display spatial data

GIS is an integration of five basic components

Data for GIS

• Base Maps Political boundaries, postal areas Municipal boundaries Highways, streets, rivers

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Lakes, parks, landmarks • Business Maps and Data

– Business/Customer locations – Census/Demography – Consumer products, financial services – Health care, real estate

• Environmental Maps and Data – Environmental risk – Satellite imagery, weather – Topography, natural resource – General Reference Maps – World boundaries – Country boundaries – City locations, time zones

GIS function is to capture, store, query, output, display and out put.

Application of GIS

• Land use Information • Urban & Township Planning • Site Location for Facility • Field of Hydrology • Geological & Geographic Maps • Atlas Maps • Plot Maps • Network Path Analysis • Field of Transportation • Tourist Information • Environmental Analysis • Health Management • Market Analysis

APPLICATION OF GIS IN LAND INFORMATION SYSTEMS (LIS) Land information is essential – to making sound land use planning decisions and protecting provincial and local interests

PRESENTATION OVERVIEW • Introduction • Data Sources • Managing Data • Using Data

Land information is significant to the success of the Planning System

Introduction: what are the key messages that we need to keep in mind about land information? Data Sources: where does data come from? Managing: where do we store data and how do we process it?

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Why LIS

As community grows land usage and the ownership changes continuously over the period of time. Planning based on these information's is a continuous process and sometimes seem to be critical. Taking decisions online effectively can be easier and faster using the technology of GIS, where the decision-maker can visualize the database before the decision pictorially too. The elementary part of a country as an “Object” is the village. The information generated from the village should flow faster to administration for proper management. The citizens should also get the information about their property with zero error. This is possible using a proper tool with GIS interface. GIS technology is a concept that makes things easier to take a decision and get information through visualization. Before taking a decision the management / administrator requires the authenticated and accurate data and a proper computer aided tool, which will incorporate & analyze data with auxiliary information and spatial information faster for the decision making. The data has to be generated and compatible application software has to be developed keeping in view suitability of the user.

Objectives

The main objective of any Land information system is to retrieve information's (like: - plot no., plot area, owner name, location) etc. about a plot mentioned in a Town, cities or village. The automation of land record can give higher accuracy in day-to-day work. The integration between land record’s data and associated map data is achieved through the GIS (Geographic information systems) technology with higher accuracy and speed i.e. if a Plot is identified in a village map, the computer can give the data relating to that Plot by accessing the database instantaneously. Similarly aggregation of land records data and associated map data, will be able to produce higher-level integrated geo-dataset To browse the information irrespective of any desired location by using the Web based Internet Technology.

Use of land records System

• Locating Plot(s) belonging to person(s) • Plot Records maintenance • Faster Updating & Presentation of Data • Planning of revenue generation • Tax Collection • Planning of irrigation pattern • Land acquisition / Disbursement • Finding land use like residential, commercial etc. • Generating a report with adequate maps • Generating a component for MIS • Accessing the attributes at the fingertips

MIS ACTIVITIES MAY INCLUDE LAND RECORD AUTOMATION • Locating plot(s) belonging to person(s). • Faster update and presentation of data (Spatial & Non-spatial)

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• Planning of revenue generation. • Planning of irrigation pattern. • Land acquisition. • Development of existing and planning of new structures. • Finding of land use like residential, commercial, industrial, water bodies etc. • Generating of reports for higher officials / management with adequate maps. • Generating a component for MIS at State/National level. • Accessing the data at the fingertips.

STAGES OF APPLICATION TOOL DEVELOPMENT The data utilized here could be divided into two groups i.e. Non-Spatial auxiliary data and Spatial map data. The non-spatial data should be in the form of external database, which facilitate the user to use the same database for other application like MIS. The database could be in Access, ORACLE. The database is stored in different tables using the concepts of RDBMS for faster and easier accessing of the data with proper multi threaded security. Hence it can be divided into MIS & GIS Activities: • MIS Activities (Activities related with Non-Spatial Data Capturing) • GIS Activities (Activities related with Spatial Data Capturing)

GIS Activities (Activities related with Spatial Data Capturing)

The data stored in GIS/or geo database consists of two sets of information; GEOMETRIC LOCATION of geographic features (that is location of point, line, or polygon) ATTRIBUTE DATA (a characteristic of a geographic feature described by nos., or characters stored in a tabular format and linked to the geographic features) The spatial data conversion process normally begins with the identification of the data source for the land base. These sources of information may range from extremely accurate surveyed maps containing no ground control references. Before starting the creation of database the source data has to be updated and verified so as to generate the accurate existing data. Sometimes the data is not clear enough to distinguish the features, which create problems for the operator and inaccurate data may get generated. As the decisions of a planner are based on the data, the inaccuracy in the base data may create problems to the planner too. So the map has to be made distinguishable before considering it as source data.

STAGES OF SPATIAL DATA CAPTURING Scanning Of Source Maps - (It is a process of converting paper/cloth map on to the digital media.) Map Preparation (The scanned Maps will be scaled on the basis of the dimensions given by the clients through rubber sheet process after which on screen digitization will be done to convert raster drawings (maps) to vector format through CAD systems (Auto Cad Map) . Digitization/vectorisation is the process of converting graphical information into a digital format. These vectorised village maps are made error free with GIS tools and are geo referenced in respect of the Survey of India Maps. An integrated single map is being generated from several cloth maps. This makes the user to access all the village maps at the same time.

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The Map is digitized into different layers, or themes. There is one layer for each set of geographic features or phenomena for which attribute information’s if available will be recorded. For example, outer boundary, road, plots, etc. and each will be stored as a separate spatial data sources, rather than trying to store them all together in one. The features of the map drawings (roads, plots, boundaries etc.) are spread across many sheets; hence one complete village may have 6-7 sheets. As logical connectivity of features of the map is very important, all the maps/sheets needs to be edge matched from all the sides with the adjacent sheets/maps. After edge matching other processes like cleaning, topology building is done along with attribute data insertion which is done in textual format. Finally a master map containing the entire village or tehsil is generated. Data Linkage (The next important activity after spatial and attribute data capturing is the process of linking the two data sets. So far these databases are in different environments and need to be integrated for mapping related queries. For integration of data there should be a unique field in both spatial as well as attributes data sets. After inserting the unique field link is made between both the databases, which provides relevant information for each geometric features. This is done through ESRI platform (Arc view software). Map Integration (The Application for integration purpose can be developed in Map Object Software through visual basic where both maps, its attribute data and external data can be visualized at a time and all the GIS related mapping Operations i.e. query analysis; thematic mapping, zooming, panning, addition and deletion of layer etc will be possible through this application.

Week 2: 24th – 28th January 2011

Lecture: Dr. Shalini Singh

ArcGIS

Exercise/Practical

ArcView Applications

• ArcMap

• ArcCatalog

• ArcToolbox

• Getting Help

ArcMap

• Primary display application • Perform map-based tasks

– Displaying – Editing – Querying – Analyzing – Charting – Reporting

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ArcCatalog

• A window into your database • Explore your data • Manage your data • Create and view data • Write or view documentation (metadata)

ArcToolbox

• Available in ArcCatalog and ArcMap • Geographic processing functions

– Analysis and conversion – Tools vary between ArcGIS products (ArcView and extensions)

Accessing the applications

• ArcView 9 shares common applications • ArcMap, ArcCatalog

– ArcToolbox and Command Line windows

Getting Help

• Tabs – Contents – Index – Search – Favorites

• Other help – Tool tips – Online Support

ArcMap

ArcMap provides tools for creating visual displays of the data, querying, and creating presentation-quality maps. ArcMap makes it easy to lay out your maps for printing, embedding in other documents, or electronic publishing. It also includes analysis, charting, reporting functions, and a comprehensive suite of editing tools for creating and editing geographic data. When you save a map, all of your layout work, symbols, text, and graphics are automatically preserved. ArcMap is the primary ArcGIS application for displaying, querying, editing, creating, and analyzing data.

ArcCatalog

The ArcCatalog application helps you organize and manage all your GIS data. It includes tools for browsing and finding geographic information, recording and viewing metadata, quickly viewing any dataset, and defining the schema structure for your geographic data layers.

ArcToolbox

The ArcToolbox window provides you with tools for data conversion, managing coordinate systems, changing map projections, and more. ArcToolbox supports easy-to-use drag-and-drop

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operations from ArcCatalog; with ArcMap, you need to browse to or type in the variables. For ArcInfo users, ArcToolbox provides additional and more sophisticated data conversion and spatial analysis tools. All ArcGIS products (ArcView, ArcEditor, and ArcInfo) are comprised of the ArcMap and ArcCatalog applications, both of which contain the Toolbox and Geoprocessing windows. ArcMap is the application for performing analysis and making maps. ArcCatalog is a tool for accessing and managing your data. ArcToolbox contains tools for data conversion and management. The Geoprocessing window allows you to write, import and run scripts, and access individual commands. The ArcGIS Desktop applications are standard Windows applications. This means that they store application data in the registry. For example, when you start ArcMap, move it to a certain location on the screen and resize it; the next time you start ArcMap it will come up at the same location and in the same size you selected. ArcGIS applications support other functions that users of Windows software often use. For example, you can use Object Linking and Embedding (OLE) to insert a Microsoft Excel spreadsheet of well sampling attributes into ArcMap, while you view the well sample locations on a map. When you need to view the spreadsheet, simply double-click the spreadsheet to start Microsoft Excel. You also have the option of hyperlinking (analogous to hotlinking in ArcView GIS 3.x) to the Excel spreadsheet if you choose to do so. Layers can be dragged from ArcCatalog and dropped into ArcMap to display the layer. You can turn on/off each toolbar and dock it anywhere you like within the application. Through a simple and intuitive customization, you can move a buttons or a tool from one toolbar to another and access their properties. The ArcGIS Desktop Help provides several methods for finding the help you need to use the software most productively. The Contents tab lets you search for information by topic. The Index tab lets you search for topics containing words from the Help index, such as Layer or Table. The Search tab lets you search the Help document for a word you specify. The Favorites tab lets you store your favorite help topics so you can easily access them when needed. Your word does not have to be in the index in order to search the document for it, but the search will take longer if it is not in the index. In ArcCatalog, ArcMap, and ArcToolbox, button and tool names are displayed when you move the mouse over them (these are called ToolTips). You can also click the What’s This? tool in ArcMap or ArcCatalog and then click on a button or tool to access additional help about it (this is called context-sensitive help). For applications like ArcMap that have graphical user interfaces, context-sensitive help is useful for finding out what all the various buttons and tools do.

Features of the ArcMap interface

• The Title bar displays the map name.

• The toolbars are dockable.

• The Table of Contents lists the Data Views and layer legends. The Table of Contents is dockable and can be resized by horizontally dragging the vertical divider between the Table of Contents and the display area.

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• The display area is where the map features draw.

• The Status bar, besides reporting the coordinates, displays a description of the selected buttons and menu items.

Data View

You will work in Data View if you want to display, query, edit, explore, and analyze data.

Layout View

When you choose to create a hard copy map, you need to move to the Layout View. This view is where you add all the other map elements, such as the north arrow, legend, scale, title, and other textual information (e.g., author, data date, map date, projection type). Once the map is complete, you can send it to a plotter or printer or export it as a graphic file.

Layers, data frames, and maps

Layers store the path to a data source as well as the display properties of that data source. A data frame is a container for layers. When you create a new empty map, a default data frame named Layers is automatically added to the top of the Table of Contents, but you can highlight and change its name. In the example above, the data frame name was changed to Europe. Like the layers they contain, data frames also have properties that you can manipulate. A map is the document that stores the data frames, layers, and any map elements such as graphics and text. A map may contain several data frames. For example, you might create a map that contains one data frame with layers that show an entire country and another data frame that displays layers of a particular region.

Data frames

Data frames let you organize your data into logical groupings, such as themes or geographic areas. You may want to consider using multiple data frames when you want to compare layers side by side or create insets and overviews that highlight a particular location. You can add as many layers as you want to a data frame; however, a data frame containing too many layers can be more difficult to work with. You may want to consider multiple data frames organized by theme or geography when you have numerous layers. When a map has more than one data frame, one of them is the active data frame. The active data frame is the one you are currently working with in the ArcMap display. For example, when you add a new layer to a map, it gets added to the active data frame. You can always tell which data frame is active because its name is shown in bold text in the Table of Contents. Of course, if a map has only one data frame, it is always the active one. To make a data frame active, right-click on the data frame and click Activate. The active data frame appears in bold font in the Table of Contents. A data frame can also be activated in the Layout View when you use your mouse to select it from the page.

Maps

The ArcMap document helps you visualize geographic information by showing you the location

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of features, which are symbolized to help you understand what they are and why they are being shown. A map can include additional information, such as graphics and map elements, that help explain its context and purpose. When you open a map document, ArcMap checks the links to the data sources. If it cannot find some data (i.e., if the source data for a layer has been deleted or renamed or if a network drive is not accessible), it does not display. The layer is still part of the map, and its name appears in the Table of Contents, but a small red exclamation mark appears right of the layer symbol. When you work in ArcMap, you are always working within an ArcMap document. The ArcMap document (MXD) lets you save the display of your data. ArcView function is Data Manipulation, Data Analysis and Data Presentation

Identify Features tool

This tool allows you to display the attributes for any feature you click on with your pointer.

Navigating the Editor toolbar

In ArcMap, editing operations are controlled through the Editor toolbar. The toolbar contains several important controls:

• Editor menu: This menu contains the commands for beginning, ending, and saving edit sessions. It also provides access to several editing operations, snapping controls, and editing options.

• Edit Tool: This tool is used to select features for editing.

• Sketch Tool: This is the primary tool for editing spatial features. It allows you to digitize in new features or modify the shape of existing features. The actual operation the tool performs is controlled by the Task list.

• Task list: You choose your desired editing operation from this dropdown list.

• Target layer: This control allows you to select the layer you want to edit.

• Split tool: Allows you to divide a select feature into two features.

• Rotate tool: Allows you to interactively rotate selected features using the mouse or an angular measurement.

• Attribute dialog: This window allows you to edit the attribute values of selected features.

• Sketch Properties: Allows you to edit the vertices of a sketch.

Select by location (spatial query)

You will often need to find features based on their geographic, or spatial, relationship to other features. Instead of using the cursor or geometric shapes to select features, you use features from one layer to select features in another layer. For this reason, Select By Location is called spatial query. When selecting features with spatial queries, you use the Select By Location dialog, available from ArcMap’s Selection menu, to create a statement about what you want to select. Your selection procedures include:

• Select features from

• Add to the currently selected features

• Remove from the currently selected features

• Select from the currently selected features

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The selected features depend on the mode used. Regardless of the mode you use, you have the option of narrowing your selection to a specific layer by checking off all the layers that you want to exclude. You can also select features using a certain buffer distance. The Select by Location dialog is where you can easily query your data using the topological relationships, which exist between features and layers.

Layer symbology in ArcMap

Drawing properties can be set within the Symbology tab of the layer’s Layer Properties dialog. In the Show panel of the Symbology tab, ArcMap has several options for creating both qualitative and quantitative thematic maps. When you chose a certain method, the properties options to the right of the Show panel change according to the type of thematic mapping method used.

Display qualitative values

Often, seeing where something is—and where it is not—can tell you exactly what you need to know. Mapping the location of features reveals patterns and trends that can help you make better decisions. The easiest way to see where features are is to draw them using a single symbol. You can draw any type of data this way. When you create a new layer, ArcMap draws it with a single symbol by default. A category describes a set of features with the same attribute value. For example, given parcel data with an attribute describing land use (e.g., residential, commercial, and public areas), you can use a different symbol to represent each unique landuse type. Drawing features this way allows you to see where features are and what category they belong to. This can be useful if you are targeting a specific type of feature for some action or policy. For instance, a city planner might use the landuse map to target areas for redevelopment. In general, look for these kinds of attributes when mapping by category or unique value:

• Attributes describing the name, type, or condition of a feature

• Attributes containing measurements or quantities that are already grouped (e.g., “0–99” or “100–199”)

• Attributes that uniquely identify features (e.g., a county name attribute could be used to draw each county with a unique color)

You can let ArcMap assign a symbol to each unique value based on a color scheme you choose, or you can explicitly assign a specific symbol to a specific attribute value.

Display quantitative values

When you want your map to communicate how much of something there is, you need to draw features using a quantitative measure. This measure might be a count, a ratio (such as a percentage), or a rank (such as high, medium, or low). You can represent quantities on a map by varying the color or symbol size you use to draw features. For example, you might use increasingly darker shades of blue to represent increasingly higher rainfall amounts or larger circles to represent cities with larger populations. Generally, you need to classify your data when you display it. You can either manually define classes or apply one of the standard classification schemes to do so automatically—just specify the number

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of classes you want to show. Once you have defined the classes, you can add more classes, delete classes, or redefine class ranges. Pie charts, bar charts, and stacked bar charts can present large amounts of quantitative data in an eye-catching fashion. For example, if you are mapping population by county, you can use a pie chart to show the percentage of the population by ethnic group for each county. Generally, you will draw a layer with charts when your layer has a number of related numeric attributes that you want to compare. Use pie charts if you want to show how much of the total amount each category takes up. Use bar charts to show relative amounts rather than a proportion of a total.

Calculating summary statistics

After making a spatial or attribute selection, you may want to calculate a simple statistics summary. This can be done by clicking the Statistics option from the Selection dropdown list. This operation invokes the Selection Statistics dialog. Here you need to select the layer, as well as the field in the feature attribute table, that you want the statistics to be calculated for. Once these are selected, a numeric statistics summary, as well as a frequency distribution chart, appears in that window.

Graphs

By displaying data values graphically, graphs simplify the often difficult task of interpreting the large amount of quantitative (numerical) attribute data associated with layers. You can represent your data and analysis results using many styles of graphs including two- dimensional and 3D graphs. ArcGIS uses graphics server software that provides a variety of chart types so you can represent your data in the clearest and most efficient manner. Values for ArcGIS graphs come directly from feature attribute tables. Some graphs are better than others at presenting certain kinds of information. Carefully consider the information you want to present before choosing a graph style. You can control most visual aspects of the graph in order to create an effective display of your data. For example, you can add titles, label axes, change the color of graph markers, or change the color and font of the chart’s text. Once you have created a graph, you can add it to a map in ArcMap’s Layout View. When placed on the layout, a graph becomes a graphic element that you can size and position as desired.

Map and design objectives

A map conveys geographic information, highlights important geographic relationships, and presents analysis results. Because most GIS users have to present their spatial data graphically to a wide variety of readers, they have also become map designers or cartographers. Any GIS analysis ends with some results that need to be communicated. You can help fulfill the purpose of your map by using proper placement of map elements and choosing symbols and cartographic elements that are tailored for the message you want to communicate. How you design a map depends on your particular objective (i.e., why you want to create a map in the first

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place). One obvious objective for creating a map is to show the results of your analysis. Other map objectives may be to simply share information, guide people, or highlight relationships. Your primary objective is usually not to create a beautiful map but to create a product that communicates effectively, efficiently, and clearly.

What other map elements are missing?

• Scale text (1:100,000)

• Other text (author name, disclaimers, projection information, date of data, date of map, and so on)

• Logos Are all these map elements really necessary? Some map elements can be ignored if other map elements or features can substitute for it. For example, a north arrow is redundant if you have neatlines shown with coordinate labels such as latitude and longitude; a north arrow and a scale bar are both redundant if you are depicting the population of the United States in a book on United States demographic statistics; a scale bar can be redundant if neatlines are shown with the proper coordinate system and units. Avoid placing any information that does not comply with the map’s objectives. These are considered ‘visual noise’ and distract from effective map communication.

Printing procedure

Follow the steps below to print your map.

• From the File dropdown list, click Print.

• In the Print dialog, point to the available printer and select the Printer Engine by clicking the Setup button. The PostScript and Windows Printer Engine drivers are available with your Windows operating system. The ArcPress Printer is a separate ESRI extension product specifically designed to facilitate high-quality map production. You choose between printer drivers in the Page Setup window.

• On the Document Properties dialog of your printer or plotter, select the paper size and source, the number of copies, the orientation, and the color appearance. Depending on which printer engine was selected, the Document Properties dialog may be different from the graphic shown in the slide.

Once you have created a map, you may want to export it from a map document to an image file. The new image can then be inserted into another document (for example, Microsoft Word or PowerPoint). Export a map by choosing Export Map from the File menu. You can export maps as several types of files. Some of these formats are: • EMF (Enhanced Metafiles) are Windows native vector graphics, raster graphics, or both.

They are useful for embedding in Windows documents because they can be resized without distortion.

• BMP (bitmap) files are simple, native Windows raster images. They do not scale as well as EMF files.

• EPS (Encapsulated PostScript) files are primarily used for vector graphics and printing, and can be sent directly as a printer file.

• PDF (Portable Document Format) files are designed to be consistently viewable across different platforms. They are commonly used for distributing documents on the Web.

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• JPEG (Joint Photographic Experts Group) files are compressed image files. They are commonly used for images on the Web because they are more compact than many other file types.

Copy map to clipboard

You may not need to create a new separate file for your map but only need to embed it into another document. Under the Edit menu, there is the option to temporarily store the map layout in the clipboard on your computer. ArcGIS (ArcView) geoprocessing tools allow you to aggregate data based on various tabular and spatial relationships. It’s easiest to think about them as a mathematical equation. There is an input or multiple inputs of data, an operation is performed on the input data that alters it in a certain way, and the data is returned as a new output. Geoprocessing is based on a framework of data transformation. A typical geoprocessing tool performs an operation on an ArcGIS dataset (such as a shapefile, feature class, raster, or table) and produces a new dataset as the result of the tool. Geocoding is the process of assigning a geographic location to point data based on a description. The description usually comes in the form of street addresses, postal codes, or cities. The geocoding service then converts this descriptive information into a point feature on a map with precise location coordinates. In order to create the point feature, a reference layer such as a street file with addresses is required. An Address Locator defines the process for converting these descriptions to points on a map by setting the parameters of the transformation. It is possible to rerun the geocoding service in order to match unmatched points interactively and thereby increase the percentage of matched points. It is important to note that geocoding is not an exact science. Each point that is inputted into the geocoding service is compared with potential candidates in a Reference Table. The points are then assigned a score based on their sameness to points in the reference table. Scores that exceed a user defined percentage are automatically matched. Points that fall below the designated grade are not matched but can be rematched interactively. Once the points have been geocoded a new output table containing 4 new auto generated columns will appear in your map view.

Model Builder

A model is a representation of reality. A model represents only those factors that are important to your work flow and creates a simplified, manageable view of the real world. ModelBuilder is an interface used to conduct geographic processing or geoprocessing functions in ArcGIS. It is part of ArcGIS’s core technology. Visually, it looks a lot like a flow chart. The power of ModelBuilder is that it allows users to automate geoprocessing functions on their data easily without writing any code. The visual nature of the interface makes it very easy to design and follow workflows and makes it a great tool for teaching students.

Joins and relates tables

ArcMap provides two methods to associate data stored in tables with geographic features: joins and relates. When you join two tables, you append the attributes from one onto the other, based

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on a field common to both tables. When you relate tables, you define a relationship between the two tables—also based on a common field—but do not append the attributes of one to the other. Instead, you can access the related data when necessary. You join two tables when the data in the tables has a one-to-one or a many-to-one relationship (e.g., you have a layer showing store locations, and you want to join a table of the latest monthly sales figures to it). You relate two tables when the data in the tables has a one-to-many or many-to-many relationship (e.g., your map displays a parcel database, and you have a table of owners; a parcel may have more than one owner, and an owner may own more than one parcel). Joins and relates are reconnected whenever you open the map. This way, if the underlying data in your tables changes, it is reflected in the join or relate. A join is used to append the fields of one table to those of another through an attribute or field common to both tables. Within ArcMap, a table can be joined to a preexisting dataset to provide a spatial extent. Unlike a join, a relate defines a relationship between two tables. The associated data isn't appended to the layer's attribute table like it is with a join. Instead, you can access the related data when you work with the layer's attributes.

Buffering: A buffer is a zone of a specified distance around a certain feature or features. Buffers tend to be used in instances where one is trying to lessen or absorb an impact. For instance, environmentalists wanting to lessen the impact of erosion into rivers as a result of logging might suggest that a 500 metre buffer be placed around the rivers. This would prevent any logging within 500 metres of the river. In addition, buffers can also be used to assess and closely analyze impacts, MapTips and hyperlinks: If you have MapTips set for a layer, when you move the mouse pointer over a feature in the layer, a rectangular box containing textual information appears. The MapTip text comes from a field in the attribute table of that layer. You have to set which field you want attribute values to be reported from when using the MapTips. You can display Web pages accessed over the Internet and documents (such as a text file or image) or run a macro (script). You can dynamically create hyperlinks as you browse your map, or you can store hyperlinks with your data in an attribute field. When you click on a feature, ArcMap determines which program is needed to display the hyperlink. If you specify a Web address, ArcMap launches your default Web browser and displays the page. If you specify a different type of document (e.g., a text document), ArcMap displays it using its native program (such as Notepad or another text editor). The Hyperlink Manager allows you to set more than one hyperlink per feature; these are called Dynamic Hyperlinks. If you are creating maps that people will access interactively or if you want to explore your data before you do analysis, MapTips and hyperlinks are useful ways to present more information

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about the map’s features.

Layering

One of the main features of a layer is that it can exist outside your map as a file on disk. This makes it easy for others to access the layers you've built. When you save a layer to disk, you save everything about the layer, such as the symbolization and labeling. When you add a layer file to another map, it will draw exactly as it was saved. Others can drop those layers onto their maps without having to know how to access the database or classify the data; this can be helpful when sharing data stored in a multiuser geodatabase with nontechnical staff members. You can share layers over the network as well as e-mail layers, along with the data, to people or enclose the layer within the data's metadata. The layer file that is created will reference its data source using the Data Source Options setting currently specified for the map on the Document Properties dialog box (accessed from the ArcMap File menu). By default, this setting specifies that data sources will be referenced with their full path. GIS Information about spatial features is typically stored in tables using a database management system. Typically the databases are stored as spreadsheets with each row or record corresponding to one feature such as a point, line, or polygon. Each column in the table corresponds to a feature attribute. The table columns are typically called fields or items. Each column in a table typically has the following characteristics:

• Item Name. The item name is simply the name of the table column.

• Item Type. The item types most commonly used are binary integer (B), floating point (F), character (C), and date (D). Examples of binary integer items include categorical attributes such as soil texture class, vegetation class, or road surface type. Examples of floating point items include quantitative values such soil pH, tree diameter, or road length. Examples of character items include names such as soil order, plant genus/species, or street name.

• Item Width. This refers to the number of bytes required to store each item. The most basic storage unit for computers is a Bit (or Binary Digit). A bit has two possible states, either a 0 or 1. Eight bits together make up a Byte.

Lecture: Dr Shalini Singh

Exploring GIS concepts

Exercise/Practical

Database: A database is an integrated set of data on a particular subject. DBMS: “A database management system is a software application designed to organize the efficient and effective storage and access of data.” RDBMS: “A relational DBMS comprises a set of tables, each a 2-D array of records containing attributes about the objects under study”

Geodatabase and Feature Dataset A geodatabase is a relational database that stores geographic data. At its most basic level, the

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geodatabase is a container for storing spatial and attribute data and the relationships that exist among them. In a geodatabase, which is a vector data format, features and their associated attributes can be structured to work together as an integrated system using rules, relationships, and topological associations. The basic building blocks of a geodatabase are feature (object) classes, feature datasets, and non spatial tables. Using these, you can build more complex objects in your geodatabase. Associations among geodatabase components created based on spatial relationships (topology) or attributes (relationship classes).

• A geodatabase is a relational database that stores geographic information. • A feature dataset is a collection of feature classes that share the same spatial reference

frame. • Why geodatabases? To establish and store relationships based on tabular information. • Why feature datasets? To establish and store relationships based on geographic information. • A feature class is a collection of features that share the same geometry type (point, line, or

polygon) and spatial reference. • A feature dataset is a collection of feature classes. All the feature classes in a feature dataset

must have the same spatial reference. • A non spatial table contains attribute data that can be associated with feature classes. A feature class is a collection of geographic features with the same geometry type, attributes, and spatial reference. Feature classes can also store annotation (text or graphics that can be individually selected, positioned, and modified). Feature classes may exist independently in a geodatabase as standalone feature classes or they can be grouped into feature datasets. A feature dataset contains a group of feature classes that share the same spatial reference. That is, the feature classes must have the same coordinate system and their features must fall within a common geographic extent. • Feature datasets are primarily used to store feature classes that have topological relationships,

such as connectivity, adjacency, or containment. For example, streams in a particular watershed are connected to rivers; therefore, streams and rivers are topologically related.

• In order for a geodatabase to maintain topological relationships among feature classes, the feature classes must reside in the same feature dataset.

There are only two types of tables that you interact with directly: feature class and non spatial • Both types are created and managed in Arc Catalog and edited in Arc Map. Both display in

the traditional row-and-column format. The difference is that feature class tables have one or more columns that store feature geometry.

• Non spatial tables contain only attribute data (no feature geometry) and display in Arc Catalog with the table icon. They exist in a geodatabase as standalone tables, and they can be associated with other tables or feature classes. When a non spatial table is associated with a feature class, you can query, select, and symbolize features based on the data stored in the

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non spatial table. In a geodatabase, relationship classes provide a way to model relationships that exist between real-world objects such as parcels and buildings or streams and water sample data. For example, in the real world, buildings are always located on parcels. When the ownership of a parcel changes, the ownership of the buildings on the parcel usually changes as well. If a building footprint changes, it can affect the parcel (the value of the parcel improvements may increase or decrease). By setting up a relationship class between these two feature classes, you can help make sure that when a feature in one of the feature classes changes, related features in the other feature class are updated

The GIS Data Model

The purpose of the model is to allows the geographic features in real world locations to be digitally represented and stored in a database so that they can be abstractly presented in map (analog) form, and can also be worked with and manipulated to address some problem

Geodatabase model

A geodatabase (short for geographic database) is a physical store of geographic information (spatial, attribute, metadata, and relationships) inside a relational database management system (RDBMS).

• Stores geographic coordinates as one attribute in a relational database table • Uses MS Access for “Personal Geodatabase” (single user) • Uses Oracle, MySQL, PostgreSQL, Sybase, Ingress or other commercial relational

databases for “Enterprise Geodatabases” (many simultaneous users)

Relational Database Management System (RDBMS)

• A type of database in which the data can be spread across several tables that are related together. Data in related tables are associated by shared attributes. Any data element can be found in the database through the name of the table, the attribute (column) name, and the attribute values that uniquely identify each row. In contrast to other database structures, an RDBMS requires few assumptions about how data is related or how it will be extracted from the database. As a result, the data can be arranged in different combinations.

• All data (vector, raster, address, measures, CAD, etc.) is stored together in a commercial off-the-shelf RDBMS. This means that organizations can have an integrated data management policy covering all data, which can significantly simplify support and maintenance, and reduce costs.

• Geodatabases offer many advantages for GIS users. The range of functionality available is extensive and includes centralized data storage, support for advanced feature geometry, and more accurate data entry and editing through the use of subtypes, attribute domains, and validation rules

• Geodatabases can be created and managed easily using the standard tools in ArcCatalog, and ArcMap provides simple tools to work with geodatabases. The advanced features described above are also available for those users with demanding application requirements

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Geodatabase objects

Basic objects:

- feature classes, - feature datasets, - nonspatial tables.

Complex objects building on the basic objects:

- topology, - relationship classes, - geometric networks

Feature class

• A feature class is a collection of geographic objects in tabular format that have the same behavior and the same attributes.

• A feature class is a geographic feature which includes points, lines, polygons, and annotation feature class.

• Feature classes may exist independently in a geodatabase as stand-alone feature classes or you can group them into feature datasets

Feature datasets

• A feature dataset is composed of feature classes that have been grouped together so they can participate in topological relationships with each other. All the feature classes in a feature dataset must share the same spatial reference (or coordinate system)

• Edits you make to one feature class may result in edits being made automatically to some or all of the other feature classes in the feature dataset

Tables

• Feature class tables and nonspatial attribute tables.

• Both types of tables are created and managed in ArcCatalog and edited in ArcMap. Both display in the traditional row-and-column format. The difference is that feature class tables have one or more columns that store feature geometry.

• Nonspatial tables contain only attribute data (no feature geometry) and display in ArcCatalog with the table icon. They can exist in a geodatabase as stand-alone tables, or they can be related to other tables or feature classes.

Topology

• In a GIS, spatial relationships among feature classes in a feature dataset are defined by topology. You can choose whether to create topology for features.

• The primary spatial relationships that you can model using topology are adjacency, coincidence, and connectivity

• There are three types of topology available in the geodatabase: geodatabase topology (over 20 topology rules), map topology, and geometric network topology. Each type of topology is created from feature classes that are stored within a feature dataset. A feature class can participate in only one topology at a time

Object class

An object class is a collection of objects in tabular format that have the same behavior and the

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same attributes.

Relationship

• A relationship is an association or link between two objects in a database. • A relationship can exist between spatial objects (features in feature classes), non-spatial

objects (objects in object classes), or between spatial and non-spatial objects.

Geometric Network

• In the real world, examples of networks abound: streams joining together to form larger streams, pipes carrying water to homes and businesses throughout a city, and power lines carrying electricity.

• In a geodatabase, you can model each of these real-world networks with a geometric network. Starting with simple point and line feature classes, you use ArcCatalog to create a geometric network that will enable you to answer questions such as: Which streams will be affected by a proposed dam? Which areas will be affected by a water main repair? What is the quickest route between two points in the network?

• Feature classes that participate in the network are automatically converted from simple feature classes to network feature classes, and one or more attribute fields containing network information are added to the feature class table.

• There are more restrictions involved with managing network feature classes than with managing simple feature classes. You cannot rename, delete, or copy a network feature class. To perform any of these actions, you must convert the network feature class back to a simple feature class by deleting the geometric network.

• When you build a geometric network, there are a number of options you can choose from to make your network model more realistic. For example, you can:

� set the direction that resources will flow through the network � assign weights that control the speed of flow through different parts of the

network � specify rules that control how each element in the network connects to the

others • A network is a set of edges (lines) and junctions (points) that are topologically connected

to each other. • Each edge knows which junctions are at its endpoints • Each junction knows which edges it connects to

Relationship class

In a geodatabase, relationship classes provide a way to model real-world relationships that exist between objects such as parcels and buildings or streams and water sample data. By using relationship classes, you can make your GIS database more accurately reflect the real world and facilitate data maintenance. The relationships stored in a relationship class can be between two feature classes (such as buildings and parcels) or between a feature class and a nonspatial attribute table (such as streams and water quality sampling data). The relationship class is identical to a relate in ArcInfo -- the two items to be related must have a

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common attribute (primary and foreign keys). The related information will show up in ArcMap if you do an Identify on a feature, and the related data can be edited through ArcMap, ArcInfo, or ArcEditor. To use the related information for symbology purposes in ArcMap, you must create a join in ArcMap, but you will be able to choose the relationship class on which to base the join instead of defining it again.

Three types of relationship

• In a 1-1 (on-to-one) relationship, each object of the origin table/feature class can be related to zero or one object of the destination table/feature class.

• In a 1-M (one-to-many) relationship, each object in the origin table/feature class can be related to multiple objects in the destination table/feature class.

• In a M-N (many-to-many) relationship, multiple objects of the origin table/feature class can be related to multiple objects of the destination table/feature class.

Two (2) types of geodatabase

• personal

• enterprise

Personal Geodatabase

The personal geodatabase is given a name of filename.mdb that is browsable and editable by the ArcGIS, and it can also be opened with Microsoft Access. It can be read by multiple people at the same time, but edited by only one person at a time. maximum size is 2 GB. no support of raster

Multiuser Geodatabase

• Multiuser (ArcSDE or enterprise) geodatabase are stored in IBM DB2, Informix, Oracle, MySQL, PostgreSQL or Microsoft SQL Server.

• It can be edited through ArcSDE by many users at the same time, is suitable for large workgroups and enterprise GIS implementations. no limit of size. support raster data.

Geodatabase components - Raster data

• Raster data referenced only in personal geodatabase

• Raster data physically stored in multiusergeodatabse

• Raster datasets and raster catalogs A raster dataset is created from one or more individual rasters. When creating a raster

dataset from multiple rasters, the data is mosaicked, or aggregated, into a single, seamless dataset in which areas of overlap have been removed. The input rasters must be contiguous (adjacent) and have the same properties, including the same coordinate system, cell size, and data format. For each raster dataset (.img, grid, JPEG, MrSID, TIFF), ArcGIS creates an ERDAS IMAGINE file (.img).

–A raster catalog is defined as a table in the geodatabase which you can view like any other table in ArcCatalog. Each raster in the catalog is represented by a row in the table. It contains a collection of rasters that can be noncontiguous, stored in different formats, and have other different properties. In order to view all the rasters in the catalog, they must have the same coordinate system and a common geographic extent

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Grid datasets

• Cellular-based data structure composed of square cells of equal size arranged in rows and columns.

• The grid cell size and extension (number of rows and columns), as well as the value at each cell have to be stored as part of the grid definition.

Image datasets

• Supported image formats:

– ARC Digitized Raster Graphics (ADRG)

– Windows bitmap images (BMP) [.bmp]

– Multiband (BSQ, BIL and BIP) and single band images [.bsq, .bil and .bip]

– ERDAS [.lan and .gis]

– ESRI Grid datasets

– IMAGINE [.img]

– IMPELL Bitmaps [.rlc]

– Image catalogs

– JPEG [.jpg]

– MrSID [.sid]

– National Image Transfer Format (NITF)

– Sun rasterfiles [.rs, .ras and .sun]

– Tag Image File Format (TIFF) [.tiff, .tif and .tff]

– TIFF/LZW

Representing Data with Raster and Vector Models

Raster Model

• area is covered by grid with (usually) equal-sized, square cells • Attributes are recorded by assigning each cell a single value based on the majority feature

(attribute) in the cell, such as land use type. • Image data is a special case of raster data in which the “attribute” is a reflectance value

from the geomagnetic spectrum – cells in image data often called pixels (picture elements)

Vector Model

The fundamental concept of vector GIS is that all geographic features in the real work can be represented either as:

• points or dots (nodes): trees, poles, fire plugs, airports, cities • lines (arcs): streams, streets, sewers, • areas (polygons): land parcels, cities, counties, forest, rock type

Because representation depends on shape, ArcView refers to files containing vector data as shapefiles

Lecture: Vinay Shankar Prasad Sinha

Application of GIS in Watershed Analysis using ArcMap, ArcCatalog, ArcToolbar

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Geo-statistical Analysis, Conceptual model, and Practical Exercise

ModelBuilder

The ModelBuilder Window in ArcGIS provides a graphical environment in which you can build models. A model is a representation of reality. It can describe static physical and non-physical properties, work-flow processes, or both.

Why build models?

Building a model helps you manage and automate your geoprocessing work flow. Managing processes and their supporting data can be difficult without the aid of a model.

Advantages of ModelBuilder

• • Visually representing workflow (excellent for students) • • Automating workflows • • Rerunning geoprocesses unlimited times with different data and parameters • • Sharing models with other users • • Exporting models as graphics for reports It is easiest to think about ModelBuilder like a mathematical equation. There is an input or multiple inputs of data, an operation is performed on the input data that alters it in a certain way, and the data is returned as a new output. ModelBuilder starts when you create or modify a model, done through ArcToolbox. Models can be exported as graphics or scripts (models cannot loop, scripts can) Similar to ArcView 3.x and ERDAS IMAGINE ModelBuilder programmes

• Data Elements • Tool Elements • Derived Data Elements • Connectors • Text labels

• Graphics keep track of running process • Run = running process • Drop shadow = process/data completed

• As data is created, it can be added to ArcMap as layers • Right-click derived data, “Add to Display”

• Variables can be set on any process • Models and scripts can be used as input to other models and scripts • Models can be documented and shared

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• It’s not just about sharing data any more!

Lecture: Vinay Shankar Prasad Sinha

M.A. (Geog.), P.G.Dip.(R.S.), M.Tech.(R.S.) “Research Associate”

The Energy and Resources Institute, New Delhi.

Exercise/Practical

Brief on GIS: Basics, Component, System, Sub-system, Capture, Database type/design, Storing

Methods, Manipulation, Analysis, query, Display and Data retrieval.

GIS is defined in a multi-disciplinary as:

“GIS: Geographical Intelligent System (The system which explain the geographical phenomena

with the help of software supported intelligent power)”

Geographical information system (GIS) is an organized collection of computer hardware, software & geographic data designed to efficiently capture, store, manipulate, analyze and display all forms of geographically referenced information. GIS is an interdisciplinary tool, which has application in various fields such as Geography, Geology, Cartography, Comp. & other Engineering, Surveying, Rural & Urban planning, Agriculture, Water resources, etc.

Spatial Information

Geographical features are depicted on map by Point, Line & Polygon. POINT feature -A discrete location depicted by a special symbol or label. A single x, y coordinates. LINE feature -Represents a linear feature. A set of ordered x, y coordinates. POLYGON feature - An area feature where boundary encloses a homogeneous area.

Non-spatial Information

Representation of non-spatial (Attribute) information -consists, of textural description on the properties associated with geographical entities. Attributes are stored as a set of numbers and characters in the form of a table. Many attribute data files can be linked together through the use of common identifier code.

Component of GIS:

• Software component

• Hardware component

• Management factor

Hardware - Used to store, process and display data. Hardware capabilities affect processing speed, ease of use and type of outputs available. Software - Perform GIS operations. It contains procedures for performing various tasks. Expertise - People, who provide the intelligence to use the system, develop procedures and define the tasks of GIS.

Software component:

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Efficient Operating System: To processes large volume of data. GIS software (Raster & Vector): To Create user oriented/ Define queries Image processing software: To use old scan data or Remote Sensing data. Other programming software (Window or Command): To create object-oriente programme for different department requirements

Hardware Component:

– Basic computer component

– Scanner: To scan the maps & other geographical information.

– Plotter/ Printer: To print the Map/ Information or query about Geographical Phenomena.

– Digitizer: To convert hardcopy maps/ information in digital files.

Management Component:

To get efficient work.

To get maximum outputs.

To get proper maintenance of hardware & software component.

Capabilities of GIS

Uses of geographic information technology vary widely. There has been an explosion of GIS applications in spatial data analysis over the past few years. There are very good example to solve geo-scientific problems. Three major capabilities of GIS are: Cartographic capability

Data management capability

Analytical capability

Cartographic capability allows accurate maps and engineering drawing to be produced efficiently. This capability includes digitizing (converting analog products to digital form), graphic display generation, interactive graphic manipulation (e.g. add, modify, delete, create window) and plotting. Data management capability enables the efficient storage and manipulation of geographic data, both graphic and non-graphic. Storage and retrieval of non-geographic data is linked to graphic images. It is sometimes called Attribute Processing. Attribute processing can select data and produce graphic and reports on the basis of attribute value. Analytical capability permits sophisticated processing and interpretation of spatial data. Collectively, these capabilities give managers an enhanced ability to manipulate and use data more effectively. Graphic representations are especially powerful for conveying information.

GIS As a Set of Interrelated Sub-Systems

GIS is a combination of various sub-systems. They are as follows: Data processing system:

Data Analysis Subsystem:

Information Use subsystem:

Database management

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A data base here refer to a computerized collection of related information stored in such a way that retrieval can be performed by linking various pieces of information together. It consists of one or more data files, which are collection of related information treated as one unit on a computer. Databases are managed and accessed via software termed Database Management System (DBMS). Data base management system (DBMS) is a set of computer programs for organizing the information in a database. Typically, a DBMS contains routines for data input, verification, storage, retrieval and combination. The combination of hardware, software and the database itself is referred to as a data base system. The main characteristic of Geographical database is its spatial nature. A spatial database is a collection of spatially referenced data that act as a model of reality. All the basic data types in geography / geology are spatially distributed such as geomorphological feature, rock type, well site, lineaments, roads etc. Hence Geographic Information System provides an excellent tool to design, implement and manage geographical data in a most efficient manner. Database Design: As in normal activity, GIS database needs to be properly designed to cater to the needs of specific application. The design should define a comprehensive framework of database, identification of essential and correct data elements, updating procedure etc. Generally, the database design include-

Conceptual design: It is independent of software and hardware and defines the application needs and the objective of GIS database- Specific to the ultimate use of GIS database, E.g., GIS database for natural resource management, Ground water management etc. Defining level of database indicates the scale or level of data contents of database Spatial elements of database – defining the spatial database (primary & derived) that will populate the database. Non-spatial elements of the database – defining the non-spatial datasets (primary & derived) that will populate the database. Sources of spatial and non-spatial data- identifying the data collection and data generation activity.

Logical design:

It pertains to the logical definition of the database and is specific to a GIS package. It includes- Defining the coordinate system of the database – All spatial elements can be referenced to uniform coordinate system. Defining spatial framework – Latitude /Longitude graticules, spatial files design, identification of registration points.

Defining attribute codes and their description

Spatial database normalization-

• Identification of master templates

• Ensuring that the features of various elements are coordnate coincident. Tolerance definitions-

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• Coordinate movement tolerance – Defines the position and is a function of scale.

• Weed Tolerance- Minimum separation between coordinates while digitization.

• MSU- Maximum spatial units, indicating the smallest representative area. Feature having less area than MSU can be aggregated.

• Defining the linkage between spatial and non-spatial database through a code. Physical design: It is based on experience and pertains to-

• Disk space requirement.

• Load of database.

• Access and speed requirement.

• Platform related aspects.

Database characteristics:

It should be contemporaneous – should contain information of the same vintages for the entire measured variable.

• It should be positionally accurate.

• The category of information and sub categories within them should contain all the data needed to analyze or model the behavior of the resource using conventional methods and model.

• Exactly compatible with other information that may be compared with it

• Internally accurate, portraying the nature of phenomena without error requires clear definition of phenomena that are included.

• Readily updated on a regular schedule.

• Accessible to whoever needs it.

GIS DATA MODELS

Geographical variations are infinitely complex and must be represented in terms of discrete objects. Conversion of real world geographical variation into discrete objects is done through data models. It represents the linkage between the real world domain of geographic data and computer representation of these features.

Raster data model:

• Divides the entire area into rectangular grid cells, where x = y distance

• Each cell contains a single value and every location corresponds to a cell.

• One set of cells and associated values is a LAYER / CHANNEL.

Vector data model:

• Uses discrete line segments or points represented by their explicit x, y coordinates to identify locations.

• Discrete objects (boundaries, streams) are formed by connecting line segments.

• Area is defined by set of line segments.

IMPORTANT GIS ANALYSIS (Line/Area)

• SPATIAL ANLYSIS (Lineament Direction or filter)

• ROUTE / NETWORK ANALYSIS

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• LINE BUFFER

• SURFACE ANALYSIS (TIN OR GRID)

• IDENTITY ANALYSIS (Line in polygon)

• INTERSECT ANALYSIS (Line in polygon)

• NEAREST ANALYSIS

• APPEND

• CLIP

• ERASE

• SPLIT

• LINE OF SIGHT

• VISIBILITY ANALYSIS

• CONTOUR GENERATION

• PROFILE

Working with Grid feature:

This feature represent by number of cells in X & Y direction with equal size. Z-direction represents the attribute of spatial feature.

IMPORTANT GIS ANALYSIS

• DIGITAL ELEVATION MODEL

• TOPOGRAPHICAL ELEVATION MODEL

• SLOPE DIRECTION

• RUN OFF ANALYSIS (FLOW DIRECTION)

• FLOW ACCUMILATION.

• DARCY FLOW VECTOR.

• WATERSHED DEFINATION.

Manipulation & Analysis

Geographical analysis allows studying the real world process by developing and applying manipulation and analysis criteria.

Step for performing geographical analysis:

For doing any kind of analysis for arriving at desired results, the goals and objectives must be define which will set the sequence of analysis functions to be performed on the data. Generally, following steps are involved –

• Establish objectives and analysis criteria.

• Prepare data for spatial operations.

• Perform spatial operations.

• Perform tabular analysis.

• Evaluate and interpret the results.

• Refine the analysis if necessary.

• Produce final maps and tabular reports.

Topological Overlays:

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• Spatial Join • Identity • Intersect • Union • Feature Extraction • Clip • Erase • Reselect • Feature Merging • Dissolve • Eliminate • Proximal Operations • Buffer • Coordinate Transformation • Transform • Project • Map Database Merging and Splitting • Mapjoin • Split

DATA MODELS:

Geographical variations are infinitely complex and must be represented in terms of discrete objects. Conversion of real world geographical variation into discrete objects is done through data models. It represents the linkage between the real world domain of geographic data and computer representation of these features.

Raster data model:

Divides the entire area into rectangular grid cells, where x = y distance Each cell contains a single value and every location corresponds to a cell. One set of cells and associated values is a LAYER / CHANNEL

Vector data model:

Uses discrete line segments or points represented by their explicit x, y coordinates to identify locations. Discrete objects (boundaries, streams) are formed by connecting line segments. Area is defined by set of line segments.

Raster data structure:

• Chain Code

• Block Code

• Quadra tree

• Run length

Week 3: 31st January – 4th February 2011

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Lecturer: Nimesh Dugar

MapInfo

Exercise/Practical

As with most other GIS packages, several files are required to allow the user to open a data set for viewing within Mapinfo Professional. The most basic view would be the browser view only. This environment provides storage of attribute or object data and is represented like a spreadsheet. Only data can be seen in a tabular format with this environment, no geographic information is available at this point. Minimum files required for the basic Mapinfo browser environment:

• .DAT (The file which stores the attribute data. This usually a dBase III DBF file)

• .TAB (The ASCII file which is the link between all other files and holds information about the type of data file )

To view geographic information (the graphic representation of data) in Mapinfo Professional, two additional files are required and added to the basic requirements for simply viewing data. Minimum files required to view a map with the data previously discussed: .ID (Stores information linking graphic data to the database information. This contains a 4-byte integer index into the MAP file for each feature) .MAP (Stores the graphic and geographic information needed to display a map on the users screen) .IND (Optional index files for tabular data. This is present if any fields are indexed). The basic file set for viewing data and its graphic representation within Mapinfo Professional requires a minimum of four files, the *.DAT, *.TAB, *.ID and *.MAP If you have only textual information and there are no graphic objects, then a minimum of two files is needed, *.DAT and *.TAB. If one opens, *.TXT, *.XLS *.WK*, *.MDB, then MapInfo creates a .TAB file that contains the definition of file, and data structure, so next time one can open the TAB file only. There are also temporary files created by MapInfo while there are some edits on the file. Those are

• .TDA Temporary database file

• .TIN Temporary index file

• .TMA Temporary Map File

• When using a remote table such as Oracle Locator or Spatial, if the data is downloaded to the local machine, the temporary file extensions are:

• .LDA Local Temporary database file

• .LIN Local Temporary index file

• .LMA Local Temporary Map File If MapInfo halts or in case the edited changes are not saved and the power is gone, those files remain in the computer. The software is capable of overlaying raster and vector layers on the same map; the former can be made semi-transparent, so that they can serve as more than mere backdrops.

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MapInfo is popular both in business and the public sector, where a typical user is analyzing pre-built map data layers.

Lecturer: Dr. Shalini Singh

Remote Sensing and Data Collection

Digital image Processing

Digital Numbers Exercise/Practical

Lecture: Shailendra Suman

Software Project Management

Software Development Life Cycle (SDLC) - SDLC Model

A framework that describes the activities performed at each stage of a software development project. It is a top-down approach which converts data into an operational database. The phases of SDLC are:

• Strategy and analysis

• Design

• Build and documentation

• Transition

• Production

Phase 1 Planning

Planning is the first phase of software development. In this phase the client give the details and concepts of his/her software and we plan the requirement of resources, time & budget of the proposed development.

Phase 2 - Requirements Analysis

The requirements analysis phase is concerned with capturing the requirements of the package. The requirements review is a meeting with the aim of discussing these requirements. The final output of this phase is a formal requirements document (Software Requirement Specification), which aims to freeze the requirements at this point and will serve as input to the design phase.

Phase 3 - Design & Development

The design phase is concerned with design of the software. Things to keep in mind are things like quality, flexibility (code reuse, future addition of features/functionality) etc. The final output of this phase is a formal design document (Software Design Document), which aims to freeze the design at this point and will serve as input to the coding phase. It serves as secondary function as a reference document for the code and can be particularly useful for developers that should work on the code in the future.

Phase 4 - Implementation

The implementation phase involves the actual coding/programming of the software. The output of this phase is typically the library, executables and User Manuals and additional software documentation.

Phase 5 - Testing and Integration

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The testing phase is concerned with the validation and verification of the software Unit testing is done on units and integration testing is done by including this package/unit together with other packages/units and testing them all together.

Phase 6 - Evaluation

Release the pilot of the product and client evaluates the product. If he /she require modification in the product he suggest it and we do it within a very short span of time.

Phase 7 - Release

The Release phase involves the packaging of all sub-packages, together with all relevant documentation in a suitable format for distribution.

Phase 8 - Recycle

In case of log term projects, the release phase is the staring point of recycling of the project, but in short term projects release phase is the point of sign off too.

THE SDLC WATERFALL

Small to medium database software projects are generally broken down into six stages:

• Project

• Planning

• Requirements

• Definition

• Design

• Development

• Integration

• & Test

• Installation & Acceptance The relationship of each stage to the others can be roughly described as a waterfall, where the outputs from a specific stage serve as the initial inputs for the following stage. During each stage, additional information is gathered or developed, combined with the inputs, and used to produce the stage deliverables. It is important to note that the additional information is restricted in scope; “new ideas” that would take the project in directions not anticipated by the initial set of high-level requirements are not incorporated into the project. Rather, ideas for new capabilities or features that are out-of-scope are preserved for later consideration. After the project is completed, the Primary Developer Representative (PDR) and Primary End-User Representative (PER), in concert with other customer and development team personnel develop a list of recommendations for enhancement of the current software.

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Lecture: Shailendra Suman

Global Positioning System (GPS)

Exercise/Practical

The Global Positioning System (GPS) was designed for military applications. Its primary purpose was to allow soldiers to keep track of their position and to assist in guiding weapons to their targets. The satellites were built by Rockwell International and were launched by the U.S. Air Force. The entire system is funded by the U.S. government and controlled by the U.S. Department of Defense. The total cost for implementing the system was over $12 billion. A GPS satellite. The GPS constellation of satellites consists of at least 24 satellites – 21 primary satellites and 3 orbiting spares. They orbit the earth at an altitude of 17,500 KM (10,900 miles) at a speed of 1.9 miles per second between 60°N and 60°S latitude. Each satellite weighs 1900 lbs and is 17 feet (5.81 meters) wide with solar panels extended. The satellites orbit the earth twice a day. This guarantees that signals from six of the satellites can be received from any point on earth at almost any time.

GPS Satellites

The GPS Operational Constellation consists of 24 satellites that orbit the Earth in very precise

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orbits twice a day. GPS satellites emit continuous navigation signals.

Receivers and Satellites

GPS units are made to communicate with GPS satellites (which have a much better view of the Earth) to find out exactly where they are on the global scale of things.

GPS Signals

Each GPS satellite transmits data that indicates its location and the current time. All GPS satellites synchronize operations so that these repeating signals are transmitted at the same instant.

Satellite frequencies

• L1 (1575.42 MHz): Mix of Navigation Message, coarse-acquisition (C/A) code and encrypted precision P(Y) code, plus the new L1C on future Block III satellites.

• L2 (1227.60 MHz): P(Y) code, plus the new L2C code on the Block IIR-M and newer satellites since 2005.

• L3 (1381.05 MHz): Used by the Nuclear Detonation (NUDET) Detection System Payload (NDS) to signal detection of nuclear detonations and other high-energy infrared events. Used to enforce nuclear test ban treaties.

• L4 (1379.913 MHz): Being studied for additional ionospheric correction.

• L5 (1176.45 MHz): Proposed for use as a civilian safety-of-life (SoL) signal (see GPS modernization). This frequency falls into an internationally protected range for aeronautical navigation, promising little or no interference under all circumstances. The first Block IIF satellite that would provide this signal is set to be launched in 2010

• GPS and remote sensing imagery are primary GIS data sources, and are very important GIS data sources.

• GPS data creates points (positions), polylines, or polygons

• Remote sensing imagery and aerial photos are used as major basis map in GIS

• Information digitized or classified from imagery are GIS layers

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Space Segment

The nominal GPS Operational Constellation consists of 24 satellites that orbit the earth in 12 hours. There are often more than 24 operational satellites as new ones are launched to replace older satellites. The satellite orbits repeat almost the same ground track (as the earth turns beneath them) once each day. The orbit altitude is such that the satellites repeat the same track and configuration over any point approximately each 24 hours (4 minutes earlier each day). There are six orbital planes, with nominally four SVs (Satellite Vehicles) in each, equally spaced (60 degrees apart), and inclined at about fifty-five degrees with respect to the equatorial plane. This constellation provides the user with between five and eight SVs visible from any point on the earth.

Control Segment

The Master Control facility is located at Schriever Air Force Base (formerly Falcon AFB) in Colorado. These monitor stations measure signals from the SVs which are incorporated into orbital models for each satellites. The models compute precise orbital data (ephemeris) and SV clock corrections for each satellite. The Master Control station uploads ephemeris and clock data to the SVs. The SVs then send subsets of the orbital ephemeris data to GPS receivers over radio signals.

User Segment

The GPS User Segment consists of the GPS receivers and the user community. GPS receivers convert SV signals into position, velocity, and time estimates. GPS receivers are used for navigation, positioning, time dissemination, and other research.

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Coordinate System and Height

• GPS use the WGS 84 as datum

• Various coordinate systems are available for chosen

• GPS height (h) refers to ellipsoid surface, so it is a little difference from the real topographic height (H). the difference is the geoid height (N), the approximate Mean Sea Level. Some newer GPS units now provide the H by using the equation H=h-N (N from a globally defined geoid – Geoid99)

Lecture: Shailendra Suman

Principles of Remote Sensing (RS)

• To be of greatest value, the original remotely sensed data must usually be calibrated in two distinct ways:

• It should be geometrically (x,y,z) and radiometrically (e.g, to percent reflectance) calibrated so that remotely sensed data obtained on different dates can be compared with one another.

• The remotely sensed data must usually be calibrated (compared) with what is on the ground in terms of biophysical (e.g., leaf-area-index, biomass) or cultural characteristics (e.g., land use/cover, population density).

• Fieldwork is necessary to achieve both of these objectives . Thus, a person who understands how to collect meaningful field data about the phenomena under investigation is much more likely to use the remote sensing science wisely.

Remote Sensing

Definition: “The measurement or acquisition of information of some property of an object or

phenomenon, by a recording device that is not in physical or intimate contact with the object or

phenomenon under study” (Colwell, 1997).

Remote sensing data collection

ASPRS adopted a combined formal definition of photogrammetry and remote sensing as

(Colwell, 1997): “the art, science, and technology of obtaining reliable information about

physical objects and the environment, through the process of recording, measuring and

interpreting imagery and digital representations of energy patterns derived from non-contact

sensor systems”.

A remote sensing instrument collects information about an object or phenomenon within the instantaneous-field-of-view (IFOV) of the sensor system without being in direct physical contact with it. The sensor is located on a suborbital or satellite platform.

Remote sensing is the science (and to some extent, art) of acquiring information about the Earth's surface without actually being in contact with it. This is done by sensing and recording reflected or emitted energy and processing, analyzing, and applying that information.

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Elements of a Remote Sensing System

• Information User • Area or scene of interest • Sensing Device • Data Recorder • Information Production System • Information Delivery System

A remote sensing system

• Energy source (EMR) • Platform • Sensor • Data recording / Transmission • Ground receiving station • Data processing • Expert interpretation / data users

Types of sensors

• CAMERA

• SCANNER

• RADAR

Scanning systems can be used on both aircraft and satellite platforms and have essentially the same operating principles. A scanning system used to collect data over a variety of different wavelength ranges is called a multispectral scanner (MSS), and is the most commonly used scanning system. There are two main modes or methods of scanning employed to acquire multispectral image data

• Across-track scanning

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• Along-track scanning

ACROSS-TRACK SCANNER: scan the Earth in a series of lines. The lines are oriented perpendicular to the direction of motion of the sensor platform (i.e. across the swath). Each line is scanned from one side of the sensor to the other, using a rotating mirror (A). As the platform moves forward over the Earth, successive scans build up a two-dimensional image of the Earth´s surface.

The incoming reflected or emitted radiation is separated into several spectral components that are detected independently. The UV, visible, near-infrared, and thermal radiation are dispersed into their constituent wavelengths. A bank of internal detectors (B), each sensitive to a specific range of wavelengths, detects and measures the energy for each spectral band and then, as an electrical signal, they are converted to digital data and recorded for subsequent computer processing. The IFOV (C) of the sensor and the altitude of the platform determine the ground resolution cell viewed (D), and thus the spatial resolution. The angular field of view (E) is the sweep of the mirror, measured in degrees, used to record a scan line, and determines the width of the imaged

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swath (F).

Satellites, because of their higher altitude need only to sweep fairly small angles (10-20º) to cover a broad region. Because the distance from the sensor to the target increases towards the edges of the swath, the ground resolution cells also become larger and introduce geometric distortions to the images. Also, the length of time the IFOV "sees" a ground resolution cell as the rotating mirror scans (called the dwell time), is generally quite short and influences the design of the spatial, spectral, and radiometric resolution of the sensor. ALONG -TRACK SCANNER: It uses the forward motion of the platform to record successive scan lines and build up a two-dimensional image, perpendicular to the flight direction. Along track scanners use a linear array of detectors (A) located at the focal plane of the image (B) formed by lens systems (C), which are "pushed" along in the flight track direction.

Each individual detector measures the energy for a single ground resolution cell (D) and thus the size and IFOV of the detectors determines the spatial resolution of the system. A separate linear array is required to measure each spectral band or channel. For each scan line, the energy detected by each detector of each linear array is sampled electronically and digitally recorded. There are two types of scanners, black and white and multispectral. The scanners are MADE UP OF CHARGE COUPLE DEVICES AND/OR MIRRORS and OUTPUT AS GOOD AS CCD SENSITIVITY The TECHNIQUES used to capture data are either WHISK BROOM or PUSH BROOM A PUSHBROOM SCANNER HAS AN ARRAY OF CCDs CAPABLE OF ACCEPTING REFLECTED ENERGY FROM WHOLE OF A SCAN LINE SIMULTANE-OUSLY

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Types of resolution

• SPATIAL - Discrimination by Distance • SPECTRAL - Discrimination by Wave length • RADIOMETRIC - Discrimination by energy levels • TEMPORAL - Discrimination by Time

SPATIAL RESOLUTION

IT IS THE ABILITY OF A SENSOR TO DISCRIMINATE BETWEEN TWO NEARBY OBJECTS ON THE SURFACE OF THE EARTH. IT DEPENDS ON • SENSOR SPEC - PIXEL SIZE/FOCAL LENGTH • THE DISTANCE BETWEEN THE OBJECTS - TEXTURAL/CONTRAST BETWEEN OBJECTS • SIZE OF THE OBJECTS - “REFLECTANCE” OF THE OBJECTS IN RELATION TO THE SURROUNDING AREA

GROUND SEGMENT

• DATA ACQUISITION • SATELLITE CONTROL • ERROR CORRECTIONS • DISSEMINATION

Advantages of Remote Sensing

• Remote sensing is unobtrusive if the sensor passively records the EMR reflected or emitted by the object of interest. Passive remote sensing does not disturb the object or area of interest.

• Remote sensing devices may be programmed to collect data systematically, such as within a

9 × 9 in. frame of vertical aerial photography. This systematic data collection can remove the sampling bias introduced in some in situ investigations.

• Under controlled conditions, remote sensing can provide fundamental biophysical information, including x,y location, z elevation or depth, biomass, temperature, and moisture content.

• Remote sensing–derived information is now critical to the successful modeling of numerous natural (e.g., water-supply estimation; eutrophication studies; nonpoint source pollution) and cultural (e.g., land-use conversion at the urban fringe; water-demand estimation; population estimation) processes.

Limitations of Remote Sensing

• The greatest limitation is that it is often oversold. Remote sensing is not a panacea that provides all the information needed to conduct physical, biological, or social science research. It provides some spatial, spectral, and temporal information of value in a manner that we hope is efficient and economical.

• Human beings select the appropriate remote sensing system to collect the data, specify the various resolutions of the remote sensor data, calibrate the sensor, select the platform that will carry the sensor, determine when the data will be collected, and specify how the data are processed. Human method-produced error may be introduced as the remote sensing instrument and mission parameters are specified.

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• Powerful active remote sensor systems that emit their own electromagnetic radiation (e.g., LIDAR, RADAR, SONAR) can be intrusive and affect the phenomenon being investigated. Additional research is required to determine how intrusive these active sensors can be.

• Remote sensing instruments may become uncalibrated, resulting in uncalibrated remote sensor data.

• Remote sensor data may be expensive to collect and analyze. Hopefully, the information extracted from the remote sensor data justifies the expense.

Advantages of using satellite RS

Remotely sensed data acquired by the Earth observation satellites provides a number of benefits for studying the Earth's surface, including: • continuous acquisition of data • regular revisit capabilities (resulting in up-to-date information) • broad regional coverage • good spectral resolution (including infra-red bands) • good spatial resolution • ability to manipulate/enhance digital data • ability to combine satellite digital data with other digital data • cost effective data • map-accurate data • possibility of stereo viewing • large archive of historical data

Disadvantages

• Remote sensing has various issues – Can be expensive – Can be technically difficult – NOT direct

Remote Sensing Data Collection

There are two fundamental ways to obtain digital imagery: - acquire remotely sensed imagery in an analog format (often referred to as hard-copy) and

then convert it to a digital format through the process of digitization, and - acquire remotely sensed imagery already in a digital format, such as that obtained by the

Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor system.

Landsat ETM+ spectral bands

Band Wavelengths (µm) Ground resolution (m)

1 0.45–0.515 (blue) 30

2 0.525–0.605 (green) 30

3 0.63–0.69 (red) 30

4 0.75–0.90 (near infrared) 30

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5 1.55–1.75 (SWIR) 30

6 10.4–12.5 (thermal infrared) 60

7 2.09–2.35 (SWIR) 30

Pan 0.52–0.90 15

Lecture: Dr. Shalini Singh

ERDAS IMAGINE

Exercise/Practical

The ERDAS IMAGINE system incorporates the functions of both image processing and GIS. These functions include importing, viewing, altering, and analyzing raster and vector data sets. It is a complete Image Processing and GIS package and employs a graphical user interface for:

• Reference imagery to the earth’s surface

• Measure imagery to collect vector, point and area data and create digital terrain models

• Analyze the results to draw conclusions about the processes and activities affecting your area of study

• Present imagery and geospatial information in 2D and 3D environments

• Update GIS with accurate geospatial data

• Directly read over 50 formats

• Import / export over 100 formats

• Geometrically correct to hundreds of map projections

• Single-frame orthorectification

• Rapidly reproject from one projection to another

• Mosaic images

• Image to image registration

• Resampling nearest neighbor

• Radiometric correction

• Striping and banding

• Atmospheric correction

• Linear stretching

Week 4: 7th – 11th February 2011

Lecture: Shailendra Suman

Space Segment Consideration (continued from week 3)

Thermal Infrared Remote Sensing (continued from week 3) Lecture: Ritesh Kumar, “ M. Tech. Remote Sensing”, Birla Institute of Technology (BIT)

Mesra, Ranchi

Active microwave (RADAR)

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Passive and Active Remote Sensing Systems

Passive remote sensing systems record electromagnetic energy that is reflected (e.g., blue, green, red, and near-infrared light) or emitted (e.g., thermal infrared energy) from the surface of the Earth. There are also active remote sensing systems that are not dependent on the Sun’s electromagnetic energy or the thermal properties of the Earth. Active remote sensors create their own electromagnetic energy that 1) is transmitted from the sensor toward the terrain (and is largely unaffected by the atmosphere), 2) interacts with the terrain producing a backscatter of energy, and 3) is recorded by the remote sensor’s receiver. The most widely used active remote sensing systems include: • Active microwave (RADAR), based on the transmission of longwavelength microwaves (e.g., 3 – 25 cm) through the atmosphere and then recording the amount of energy back-scattered from the terrain; • LIDAR, which is based on the transmission of relatively shortwavelength laser light (e.g., 0.90 mm) and then recording the amount of light back-scattered from the terrain; and • SONAR, which is based on the transmission of sound waves through a water column and then recording the amount of energy back-scattered from the bottom or from objects within the water column.

Sending and Receiving a Pulse of Microwave

EMR - System Components

• The pulse of electromagnetic radiation sent out by the transmitter through the antenna is of a specific wavelength and duration (i.e., it has a pulse length measured in microseconds, m sec). • The wavelengths are much longer than visible, near-infrared, mid-midinfrared, or thermal infrared energy used in other remote sensing systems. Therefore, microwave energy is usually measured in centimeters rather than micrometers. • The unusual names associated with the radar wavelengths (e.g., K, Ka, Ku, X, C, S, L, and P) are an artifact of the original secret work on radar remote sensing when it was customary to use the alphabetic descriptor instead of the actual wavelength or frequency. Primary Advantages of RADAR - Remote Sensing of the Environment Active microwave energy penetrates clouds and can be an all-weather remote sensing system. • Synoptic views of large areas, for mapping at 1:25,000 to 1:400,000; cloud-shrouded countries may be imaged. • Coverage can be obtained at user-specified times, even at night. • Permits imaging at shallow look angles, resulting in different perspectives that cannot always be obtained using aerial photography. • Senses in wavelengths outside the visible and infrared regions of the electromagnetic spectrum, providing information on surface roughness, dielectric properties, and moisture content.

May penetrate vegetation, sand, and surface layers of snow.

• Has its own illumination, and the angle of illumination can be controlled. • Enables resolution to be independent of distance to the object, with the Secondary

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Advantages of RADAR Remote Sensing of the Environment

• size of a resolution cell being as small as 1 x 1 m.

• Images can be produced from different types of polarized energy (HH, HV, VV, VH).

• May operate simultaneously in several wavelengths (frequencies) and thus has multi-frequency potential.

• Can measure ocean wave properties, even from orbital altitudes.

• Can produce overlapping images suitable for stereoscopic viewing and radargrammetry.

• Supports interferometric operation using two antennas for 3-D mapping.

Radar Nomenclature

• Nadir • Azimuth flight direction • Range (near and far) • Depression angle (g) • Look angles (f) • Incidence angle (q) • Altitude above-ground-level, H • Polarization

Azimuth Direction

• The aircraft travels in a straight line that is called the azimuth flight direction.

• Pulses of active microwave electromagnetic energy illuminate Azimuth Direction strips of the terrain at right angles (orthogonal) to the aircraft’s direction of travel, which is called the range or look direction.

• The terrain illuminated nearest the aircraft in the line of sight is called the near-range. The farthest point of terrain illuminated by the pulse of energy is called the far-range.

Range Direction

• The range or look direction for any radar image is the direction of the radar illumination that is at right angles to the direction the aircraft or spacecraft is traveling.

• Generally, objects that trend (or strike) in a direction that is orthogonal (perpendicular) to the range or look direction are enhanced much more than those objects in the terrain that lie parallel to the look direction. Consequently, linear features that appear dark or are imperceptible in a radar image using one look direction may appear bright in another radar

image with a different look direction.

Lecture: Dr. Shalini Singh

ArcGIS

Introduction to Image Interpretation

Digital Image Processing

Digital Image Enhancement

Digital Image Classification

ERDAS Imagine

Practicals on Image to image registration, Re-sampling nearest neighbor, striping and

banding, Atmospheric correction, Classification, Image manipulation, Spectral

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Enhancement, Radiometric Correction, Modeler using ERDAS

Remote Sensing and Data Collection

Lecture: Dr. Shalini Singh

Digital image Processing and Classification

Linear Stretching

Change Detection

Exercise/Practical

Lecture: Nishant Sinha - Project Manager: Pitney Bowes Business Insight (MapInfo)

Principal Component Analysis (PCA)

Exercise/Practical

PCA is often used as a method of data compression. It allows redundant data to be compacted into fewer bands – that is the dimensionality of the data is reduced. The bands of PCA data are non-correlated and independent and are more interpretable than the source data. Principal Component Analysis (PCA)

• A statistical techniques frequently used in signal processing for data dimension reduction or data decorrelation

• Linear transformation technique related to Factor Analysis

• For given set of Image bands, new set of images produced known as Components

• Principal Component Characteristics

• Statistical abstraction of the variability inherent in the original band set

• Uncorrelated with one another

• Ordered in terms of amount of variance they explain from the original band

• Reduces dimensionality of data by keeping most significant parts of data

Application of PCA

� Means of Data compaction � For multispectral set, first two or three components explain virtually all of the original

reflectance values � Later components can be rejected to decrease volume of data with no appreciable loss

of information

� Used as noise removal technique � Later components of PCA dominated by noise effects and hence can be excluded

thereby removing noise artifacts

• Used as stripe removal technique

Week 5: 14th – 19th February 2011

Lecture: Dr. Shalini Singh

Digital Image classification

Exercise/Practical

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Digital Image classification � Multispectral classification is the process of sorting pixels into a finite number of individual

classes, or categories of data, based on their data file values. If a pixel satisfies a certain set of criteria , the pixel is assigned to the class that corresponds to that criteria.

� Multispectral classification may be performed using a variety of algorithms � Hard classification using supervised or unsupervised approaches. � Classification using fuzzy logic, and/or � Hybrid approaches often involving use of ancillary information.

Digital image classification is used in

• grouping of similar features • separation of dissimilar ones • assigning class label to pixels • resulting in manageable size of classes

Classification methods

Manual • visual interpretation • combination of spectral and spatial information

Computer assisted • mainly spectral information

Stratified • using GIS functionality to incorporate • knowledge from other sources of information

Uses

• To translate continuous variability of image data into map patterns that provide meaning to the user.

• To obtain insight in the data with respect to ground cover and surface characteristics. • To find anomalous patterns in the image data set.

Advantages

• Cost efficient in the analyses of large data sets • Results can be reproduced • More objective then visual interpretation • Effective analysis of complex multi-band (spectral) interrelationships

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Image classification methods

• It is also important for the analyst to realize that there is a fundamental difference between

information classes and spectral classes. • * Information classes are those that human beings define. • * Spectral classes are those that are inherent in the remote sensor data and must be identified

and then labeled by the analyst. There are two types of classifications, supervised and unsupervised.

Supervised image classification

• The identity and location of some of the land cover types such as urban, agriculture, wetlands are known a priori through a combination of field work and experience.

• The analyst attempts to locate specific sites in the remotely sensed data that represent homogenous examples of these known land cover types known as training sites.

• Multivariate statistical parameters are calculated for these training sites. • Every pixel both inside and outside the training sites is evaluated and assigned to the class of

which it has the highest likelihood of being a member.

Unsupervised image classification

• The identities of land cover types to be specified as classes within a scene are generally not

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known a priori because ground reference information is lacking or surface features within the scene are not well defined.

• The computer is required to group pixels with similar spectral characteristics into unique clusters according to some statistically determined criteria.

• Analyst then combine the spectral clusters into information classes.

� Clustering algorithm � User defined cluster parameters � Class mean vectors are arbitrarily � set by algorithm (iteration 0) � Class allocation of feature vectors � Compute new class mean vectors � Class allocation (iteration 2) � Re-compute class mean vectors � Iterations continue until convergence threshold has been reached � Final class allocation � Cluster statistics reporting

Supervised vs. Unsupervised Training • In supervised training, it is important to have a set of desired classes in mind, and then create

the appropriate signatures from the data. • Supervised classification is usually appropriate when you want to identify relatively few

classes, when you have selected training sites that can be verified with ground truth data, or when you can identify distinct, homogeneous regions that represent each class.

• On the other hand, if you want the classes to be determined by spectral distinctions that are inherent in the data so that you can define the classes later, then the application is better suited to unsupervised training. Unsupervised training enables you to define many classes easily, and identify classes that are not in contiguous, easily recognized regions.

Lecture: Vinay Shankar Prasad Sinha

GIS Modeling, ArcGIS3.3 and ArcGIS, Arctoolbox and ArcCatalog

Exercise/Practical

GIS Data Model

The hard part of GIS analysis is figuring out which tools to use to solve your GIS problem. POINT THEMES A point is a GIS feature that has no length or area. It has a specific X,Y coordinate and attribute information associated with that location point. POINT THEMES A point is a GIS feature that has no length or area. It has a specific X,Y coordinate and attribute information associated with that location point.

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LINE THEMES A line or arc is a GIS feature that has length but no width. Since the GIS stores each arc as a series of X,Y vertices, it can easily estimate the length of each stream arc. The GIS computes the length of each stream arc in the same units as your GIS coordinate system. And since each stream arc has a unique stream#, the GIS can determine spatial relationships among arcs. As a user, you can store information about each stream in the arc attribute table. Information could be quantities (stream pH), categories (stream class), character strings (stream name), and dates (month/day/year). Each arc is composed of a series of X, Y coordinates called vertices . NETWORK THEMES A network is a special type of line theme consisting of connected arcs such as streets, utility lines, or stream networks. DYNAMIC SEGMENTATION Sometimes important line information is not available in X, Y coordinates, but instead is recorded as measurements along lines such as mileage along a road, meters along a transect, etc. This type of information can be translated into a GIS by using a technique called Dynamic Segmentation. The technique allows for segmentation of arcs into sections without changing the arc-node structure of a line theme.

POLYGON THEMES

A polygon is a GIS feature that has an area and a perimeter. A polygon attribute table has a special record for an artificial polygon called the universe polygon . The universe polygon has an area that is the sum of the area of all polygons in the theme. It is always assigned a negative sign because it is an artificial polygon that is used by the GIS in computations.

GRID THEMES

Grids are grid cells with a fixed number of rows and columns that have several tables associated with them. Grids that are common in GIS include digital elevation and land cover grids. IMAGE THEMES Images are special grids typically derived from some remote sensing device like a satellite sensor, a digital camera, or a desktop scanner. Examples of images commonly used in remote sensing include digital orthos, satellite imagery, and scanned maps. TOOLS FOR MANAGING GIS FEATURES There are several generic tools that are applicable to managing points, lines, polygons, grids, and images. They are as follows:

• LIST—List the contents of any GIS table.

• COPY—Makes a new copy theme from any point, line, polygon, or grid theme.

• APPEND—Appends 2 or more point, line, or polygon themes.

• KILL—Deletes a user-specified point, line, polygon, or grid theme.

• RENAME—Renames a user-specified point, line, polygon, or grid theme.

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• DESCRIBE—Tells the user information about a point, line, polygon, grid, or image theme.

TOOLS FOR BUILDING ATTRIBUTE TABLES The following generic tools can be used for creating tables associated with GIS themes.

BUILD

• Builds an attribute table for a point, line, or polygon theme.

BUILDVAT

• Builds a value attribute table for an integer grid theme.

BUILDSTA

• Builds a statistics table for a grid theme.

Lecture: Nimesh Dagur

MapInfo

Exercise and practical Info Professional is a powerful Microsoft Windows–based mapping and geographic analysis application. Designed to easily visualise the relationships between data and geography. MapInfo Professional expands location intelligence:

Example Maps

• Discover trends hidden in spreadsheets and charts

• Gain new understanding of your customers and markets

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• Perform powerful data analysis and calculations

• Create custom maps and content for analysis

Use geographic insights to innovate business processes

• Manage location-based assets, people and property

• Optimize service and sales territories for greater efficiencies

• Deploy networks, infrastructure and utilities with confidence

• Map resources, plan logistics and prepare for emergencies Works and plays well with existing IT infrastructure

• Designed and tested with Windows operating systems

• Imports and exports data in a wide variety of formats

• Easily customized to meet your specific needs

Data access

MapInfo Professional provides built-in support to access and view a variety of data formats directly. This means you will be able to view your Microsoft Excel, Microsoft Access or database data, such as Oracle, Microsoft SQL Server as well as many other file formats, directly out of the box. You can also view images of virtually any format. This capability ensures that MapInfo Professional will fit into your current IT structure directly with no additional cost.

Data creation & editing

MapInfo Professional provides many CAD data creation and editing tools as well as the ability to edit your tabular data such as values and names. This means you don’t have to switch between applications. Make all your changes for maps and data in one application and save time and effort.

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Display

Thematic Map

Map display options are one of the great strengths of MapInfo Professional. You can instantly shade/change style or mark territories (using any symbol, graduated symbols, charts or graphs), boundaries, highways, fiber lines or points based on any tabular data values through a simple wizard. You can also aggregate values using statistical or any math functions to associate a symbol or a color to a point or a region based on a calculated value. For example, shade the sales territories based on number of customers. Trends based on geography reveal themselves, patterns become clear and better decisions with impact are imminent.

Data & map publishing

Sharing your results in industry formats is often as critical as the information itself. In today's IT environment, the need to have multiple publishing options is critical to meaningful communication between applications. MapInfo Professional provides a spectrum of options for this purpose. From the ability to export data to any format, to publishing large maps with legends and charts, MapInfo Professional seamlessly integrates across applications. In addition, MapInfo Professional is Web-enabled. Publish static or interactive maps through easy-to-use wizards. Share the results in a format that best fits your needs.

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Specifications

Supported Operating Systems:

• Windows® 7

• Windows® Vista

• Windows® XP

• Windows® 2008 Server

• Windows® 2008 Server with Citrix® XenApp Supported Databases: XY – i.e. Databases that store point data as X & Y numeric columns:

• Microsoft Access 2003 & 2007

• Microsoft SQL Server 2005/2008

• Microsoft SQL Server 2008 XY on a spatialized DB

• Oracle Spatial 11G, 10Gr2 (10.2.0.3)

• PostgreSQL 8.3 with PostGIS 1.3

Spatial – Databases that store map data as objects including: points lines and regions

• SQL Server 2005 with SpatialWare 4.9

• SQL Server 2008 (also called SQL Server Spatial)

• SQL Server 2008 (also called SQL Server Spatial) with SpatialWare 4.9.2

• Oracle Spatial 11G, 10Gr2

• PostgreSQL 8.3 with PostGIS 1.3 MS Office Data Types:

• MS Office 2003 – MS Excel (.XLS) & MS Access (.MDB)

• MS Office 2007 – MS Excel (.XLSX) and MS Access (.MCCDB)

Week 6: 21st – 25th February 2011

Lecture: Nimesh Dagur

Application GIS - RDBMS (SQL) – Oracle 9i

Exercises/Practical

SQL Overview covered

Oracle Database uses the SQL (Structured Query Language) database language to store and retrieve data. It includes the following categories of SQL statements:

DDL (Data Definition Language)

Used to create, alter, or drop database objects, such as schemas, tables, columns, views, and sequences. For example, statements that use the commands,ALTER, CREATE, DROP, GRANT, and REVOKE.

DML (Data Manipulation Language)

Used to query and manipulate data in existing schema objects. For example, statements that use the commands, SELECT, INSERT, UPDATE, and DELETE.

TCL (Transaction Control Language)

These statements manage changes made in DML statements. For example, statements that use the commands, COMMIT, ROLLBACK, and SAVEPOINT.

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Pseudocolumns

Values generated from commands that behave like columns of a table but are not actually stored in the table. Oracle Database supports the LEVEL and ROWNUM pseudo columns.

Functions

Operate on data to transform or aggregate it. For example, TO_DATE to transform a date column into a particular format, and SUM to total all values for a column.

Lecture: Nimesh Dagur

Introduction to Programming using Visual Studio 2005

Exercise/Practical

• Visual Basic .NET (VB.NET) is an object-oriented computer language that can be viewed as an evolution of Microsoft's Visual Basic (VB) implemented on the Microsoft

.NET framework. • A programme is an organized list of instructions that, when executed, causes the

computer to behave in a predetermined manner. Without programs, computers are useless.

• A programming language is a language used to write computer programs, which involve a computer performing some kind of computation or algorithm and possibly control external devices such as printers, robots and so on.

• Programming languages differ from natural languages in that natural languages are only used for interaction between people, while programming languages also allow humans to communicate instructions to machines

• programming languages differ from most other forms of human expression in that they require a greater degree of precision and completeness.

Types of programming Languages

• Microsoft .NET (pronounced "dot net") is a software component that runs on the Windows operating system.

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• .NET provides tools and libraries that enable developers to create Windows software much faster and easier.

• .NET benefits end-users by providing applications of higher capability, quality and security

Week 7: 28th February – 5th March 2011

Lecture: Nimesh Dagur

Loop, Object Oriented Concepts

Exercise/Practical

Accessing Databases

Accessing Databases

• Visual Basic 2005 applications often manipulate data that come from relational databases. To do this, your application needs to interface with relational database software such as Microsoft Access, Microsoft SQL Server, Oracle, or Sybase.

• Basically, a database consists of one or more large complex files that store data in a structured format.

• The database engine, in your case Microsoft Access, manages the file or files and the data within those files.

Microsoft Access Objects

• A Microsoft Access database file, which has an extension of mdb, contains tables, queries, forms, reports, pages, macros, and modules, which are referred to as database objects.

• Tables: A table contains a collection of data, which is represented by one or more columns and one or more rows of data. Columns are typically referred to as fields in Microsoft Access, and the rows are referred to as records.

• Each field in a table represents an attribute of the data stored in that table • A record in a table contains a collection of fields that form a complete set of attributes of

one instance of the data stored in that table. Connections, Data adapters, and Datasets:

• VB 2005 uses ADO.NET as primary tool for data access and data manipulation. • For accessing a database we should have a connection to the database which requires

creating a connection object. • A connection object contains a connection string that stores the name of data

provider,name of database, user name and password for connecting to the database. • A data provider is used for establishing a connection with the database,accessing data

from the database, and executing the command for data retrieval and data manipulation.

• A Data Adapter object works like a interface between a data source (database) and a dataset.

• A dataset can be termed as a logical connection of data. • A dataset object follows a disconnected architecture it means it establishes a connection

with the database ,retrieves the data, and then closes the connection with the database

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• Data contained in the dataset can be displayed in any data display controls such as data grid view, comboBox, or textbox etc.

Developing Application for Web Based GIS – the following software was used for this lecture, MapGuide, Microsoft Visual Basic 2005, Web GIS MapGuide Studio (AutoDesk) Desktop GIS MapWindowGIS MapWindowGIS and MapGuide studio (MapGuide Mastro) are SDK tools used for the development in dot Net, VB.Net and C#. The RDBMS used are SQL Server, MySQl, PostgreSQL and Oracle. MapGuide Studio is used for building maps that can be published on the web.

Week 8: 7th – 11th March 2011

Lecturer: Amjad Khan

Developing Application for Web Based GIS (continuation from week 7)

Tasks: How to fill colour of line, polygon; Find, query, theme

MapGuide and WebGIS Exercise/Practical

Lecture: Amjad Khan

MapGuide and WebGIS

Exercise/Practical

MapGuide is a software platform for distributing spatial data over the Internet or on an intranet. There are two versions of The MapGuide: MapGuide Open Source, and Autodesk MapGuide Enterprise. The collection of servers that process requests in MapGuide is called a site. You can divide the processing load between two or more servers within the site. Each site shares a single resource repository among its servers. The resource repository stores the resources that map authors use to create maps, for example, pre-defined layers for features such as roads or land parcels. In the diagram on the facing page, the site contains two servers, one of which is designated as the site server. The site server contains the resource repository. It also connects to any database server or servers. MapGuide Server provides seven services: Site, Resource, Drawing, Feature, Mapping, Rendering, and Tile. If you are using a single server, that server performs all of these services. In any case, the site server always runs the first two services, because they handle data access and manage the resources for the site. However, if you have two or more servers, you can split off the other services and allocate them to another server or servers. For example, the Mapping and Rendering services are the most processor-intensive operations and can benefit from having a dedicated server to handle them.

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• The Mapping service creates the view of a map in response to requests from the clients.

• The Rendering service creates the final map image for the AJAX viewer from input provided by the Mapping service.

Lecture: Nimesh Dagur

Use of MapObjects and Microsoft Visual Studio .NET to build a simple mapping

application using the Visual Basic (VB) language

Exercise/Practical

The following was learnt under this topic: • Create a new Windows application in Visual Studio .NET, using toolbars and other

controls standard in .NET. • Add vector and raster data to a map, and perform queries on the map data you added. • Control panning and zooming, display map layers based on scale • Draw simple graphics, and also dynamically display data.

MapObjects

• MapObjects is the mapping component software created by Environmental Systems Research Institute, Inc. (ESRI), to allow mapping functions to be included in applications developed in a variety of programming environments.

• MapObjects software is a set of mapping software components that lets you, the programmer, add dynamic mapping and geographic information system (GIS) capabilities to existing Windows applications or to build custom mapping and GIS solutions.

• MapObjects applications can be developed in any 32-bit programming environment that fully supports ActiveX,

• MapObjects comprises an ActiveX control called the Map control and a set of 46 ActiveX automation objects. It is for use in industry-standard programming environments such as Visual Basic, Visual C++, Delphi, PowerBuilder, and Visual Basic for Applications (VBA).

• ActiveX controls were originally called Object Linking and Embedding (OLE) controls • An ActiveX automation control is a software component that lets you add specific

functionality within an application that is an ActiveX container • MapObjects is not for end users. It is strictly for people who are developing applications. As

a developer, you can build applications based on MapObjects and deliver those programs to end users.

Loading MapObjects

• Once you’ve successfully installed MapObjects, the next step is to load MapObjects into a Visual Basic.NET project.

Adding a map control

• You can add one or more Map controls to any Visual Basic .NET form.

Adding a layer

• You can add layers to your map through the Map control’s Property Pages or by writing code. • MapObjects has two kinds of layers: MapLayers, which display vector data, and

ImageLayers, which display raster data.

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• You will not see any map layers drawn in the Map control at design time. When you run your project (press F5), you’ll see the map layers displayed at their full extent.

• If you don’t specify MapObjects symbol properties, such as color, size, and style, default symbol properties will be assigned for you.

Data sources for MapObjects

• Shapefiles: A shapefile is an ESRI data file format for storing geographic features in vector format. The shapefile format has represented map features by x,y coordinates

• ARC/INFO coverages: ARC/INFO coverages are topological data structures that store vector format geographic features. A coverage is stored as a directory because instead of a single file, a coverage is actually composed of a set of files, each of which contains information about a particular feature class (point, line, polygon, etc.).

• Spatial Database Engine(SDE) layers: A geographic feature in SDE consists of attributes and a geometric shape—point, line, or area. SDE stores geometric shapes as x,y coordinates. Points are recorded as a single x,y coordinate pair, lines as a series of ordered x,y coordinates, and areas as a series of x,y coordinates defining a set of line segments that have the same starting and ending point.

Industrial visit

Two companies were visited and they are indicated below:

RAMTech Cooperation

Industrial excursion to RAMTech Cooperation involved in GIS and Remote Sensing. The Company uses open source software and their front-end was developed using ASP.Net and PHP. The Relational Database Management System (RDBMS) and other software they use are PostgreSQL, PostGIS, MapServer, Google Map as base layer, open layer, ASP.Net, ArcGIS Desktop 9.3 and GeoJSON (GeoJSON – JSON Geometry and feature description). RAMTech Cooperation also uses Modeling to easy the computation and implementation of the project

MapMyIndia

www.mapmyindia.com India’s best maps and GPS NAVI-TAINMENT experience CE Info Systems (P) Ltd., a New Delhi-based ISO 9001-2000 Company founded in 1992, is India's leader in premium quality digital map data and consumer navigation services. Since 1994, through continuous field surveys and state-of-the-art mapping technology, the company has built its proprietary MapmyIndia Maps, the most comprehensive, accurate, robust and reliable navigable map dataset for all India. MapmyIndia is driving the Indian navigation industry by providing internet, mobile and in-car navigation products to end consumers directly as well as in partnership with leading international and national players. The company has been providing GIS based enterprise solutions to over 500 leading corporate and government organizations in every vertical. In 2004, MapmyIndia was short listed by NASSCOM as a showcase company for IT innovation in India. Most recently, MapmyIndia's Managing Director was elected by GPS Business News as the "World's GPS Businessman for the year 2007" for driving the navigation industry in India.

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Conclusion

The programme had 28 participants from 21 countries and only one participant from Zambia. The courses sponsored by the Indian Government accept two participants from participating countries. The programme run for 8 weeks.

The skills and knowledge gained will assist the Ministry of Agriculture and Cooperatives (Department of Agriculture) in setting up the GIS laboratory and in development applications to be use in GIS and Remote Sensing. The need for information arises at all levels, from that of senior decision makers at the national and international levels to the grass-roots and individual levels. Therefore the generation of the base map and attachments of attributes not only help the administration but also to other government and non-government organizations providing multiple usage of onetime effort. The use of the front-end tool will help in improving the revenues as well as the services benefiting time and economy.

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APPENDICES

Appendix 1: Course layout

Objectives

• The purpose of the programme is to introduce to the participants about Geographic Information System & Remote Sensing concepts.

• Contents Of The Course:

• GIS o Fundamentals of GIS, Application GIS, Advance GIS, GIS Analysis, Application

GIS Development using Map Objects.

• Remote Sensing: o Concepts Of Remote Sensing, Principles of Remote sensing, Digital Image

Processing Using ERDAS Imagine

• Specialization Through Project Work Scope of the course At the end of the course, Students will be able:

•••• To understand the GIS & Remote Sensing concepts. •••• To understand information relating to integration of GIS, Remote Sensing and

Application software development. •••• To understand about Development of GIS Applications using Client/Server Architecture

Course Content

1. Fundamentals of GIS

• Introduction to GIS

• Mapping and GIS

• Digital Representation of Geographic Data

• Vector Based GIS

• Thematic map Preparation

• GIS Analysis 2. Application GIS

• Non Spatial Database

• Client server GIS 3. Advance GIS

• Spatial Analysis and Modeling using ArcGIS

• GIS Implementation and Project Management

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4. Concepts of Remote Sensing

• Introduction to Remote Sensing (Optical, Thermal & Microwave)

• Data acquisition (aircrafts and satellites)

• Integration of GIS and Remote sensing 5. Principles of remote sensing

• Multispectral Remote sensing (multispectral scanners: whiskbroom and push broom)

• Hyper spectral Remote Sensing Analysis and interpretation of visual and digital remote sensing data

6. Digital Image Processing Using ERDAS Imagine (applications of remote sensing in land use

\ land Cover)

• Pre-processing corrections: Radiometric correction Geometric aspects

• Introduction to DIP

• Image Rectification and Restoration

• Indices and Rationing

• Image Classification

• Post Classification Smoothing

• Change Detection Analysis 7. Application Development Tools

• VB.Net

• ORACLE 9i

• SQL 8. GIS Analysis

• AutoCAD MAP

• MAP Info

• Arc View and Arc GIS

9. Non Spatial Database

• Database Concepts

• Relation between different tables

• Linking of External non spatial database Geo Database. 10. APPLICATION GIS Development

• Client/Server GIS using Oracle, VB.Net and Map Objects. Project

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Appendix 2: list of Participants

SPECIALIZED PROGRAMME ON APLICATION DEVELOPMENT

USING GIS & REMOTE SENSING- PARTICIPANTS. January-march

2011

CENTRE FOR DEVELOPMENT OF ADVANCED

COMPUTING , NOIDA, INDIA.

COUNTRY NAME EMAIL FACEBOOK SKYPE

1 CUBA Yoenis Pantoja ypantojaz@uci.cu yoenis.pantoja@gmail.com Yoenis Pantoja Zaldivar

2 SOUTH AFRICA Yashveer Ranchhod yashman18@gmail.com Yashveer Ranchhod yashman18

3

MAURITIUS

ISLAND Devendra Ramjee ramjeesona@hotmail.com sonakum70

4

MAURITIUS

ISLAND Hembal Teckmun hitecsatyam@yahoo.com

5 COLOMBIA

Elkym Alexander Mesa Sanchez ingelkym11@yahoo.es

Elkym Alexander Mesa Sanchez

6 COLOMBIA

Javier Manrique Sanabria javier.manrique.s@gmail.com Javier Manrique Sanabria

7 GUATEMALA

Gerson Solis Gutierrez gersao.g@gmail.com Gerson Solis Gutierrez

8 PALESTINE Jasim Asnaf jrimawi@gmail.com jrimawi@hotmail.com jrimawi@gmail.com jrimawi

9 UZBEKISTAN

Shakhnoza Rakhmonkulova rshakhnoza@yahoo.com rshakhnoza@gmail.com Shakhnoza Rakhmonkulova

10 MADAGASCAR

Jacq RAMAROLAHY quelin.ramarolahy@gmail.com Jacq RAMAROLAHY jacq_man

11

TRINIDAD AND

TOBAGO Kevon Rose rosekevon@hotmail.com rosekevon@hotmail.com

12

TRINIDAD AND

TOBAGO Kevon Peters kevonp@gmail.com kevonp@gmail.com

13 MYANMAR Mya Thandar Kyu myathandarkyu@gmail.com myathandarkyu@gmail.com

14 GRANADIAN Fabian Purcell fabpurcell@gmail.com

15 ANGOLA Maria Helena Loa marialoa2004@yahoo.com.br marialoa2004@yahoo.com.br

16 TANZANIA

Julius Francis Mpombo kayoghas05@yahoo.com mpombo@ifm.ac.tz

17 TUNISIA Ouali Bechir ouali.bechir@laposte.net

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18 TUNISIA Mehrez Mhamdi mehrez.mhamdi@yahoo.fr

19 ZAMBIA

Charles Bwalya Chisanga cbchisanga@gmail.com cbchisanga

20 UGANDA

Norman Francis Ntalo normanntalo@yahoo.com

21 LAO Bounmany Joh bounmany_joh@hotmail.com

22 NEPAL Sanjit Pradhan sanjit_21576@hotmail.com sanjit_21576@hotmail.com

23

PNG -Papua New

Guinea Gregory John gregoryjohn91@yahoo.com

24 AFGHANISTAN Habib Rahman habibrhr@yahoo.com

25 AFGHANISTAN Qamar Zarifi wafahamid_001@yahoo.com

26 AFGHANISTAN

Dad Mohammad Hamid Zarifi wafahamid_001@yahoo.com

27 AFGHANISTAN Mirwaislatif mirwaislatif@yahoo.com

28 SUDAN

Sudan Hassam Mohammed hasbayan@gmail.com has_bayan@hotmail.com

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