Application of GIS

Distinguishing Characteristics of a GIS vs. Other Systems

1. provides links between points, lines, areas, grids and their ATTRIBUTES in a database

2. provides algorithms for ANALYSIS of spatial data

3. “spatially intelligent” - “thinks” points, lines, areas, grids are actual spots on Earth’s surface - e.g., switching projections, computing distances

GIS “Layers,”“Themes,”“Overlays”

GIS is a multi-Billion dollar business.

• annual software revenues top $1 billion, increasing ~14% yearly

• ESRI and Intergraph software revenues account for 1/2 of industry total

• GIS industry now at $7 BILLION

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• Interactive Visualization/Analysis• Planning and Management• Spatial Data Management and Access• Environmental Risk Assessment• Multi-Dimensional Planning • Custom Applications Development For Decision Support• Web-accessible Spatial Information

Advantages of GIS Applications:

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• Facilities ManagementLarge scale and precise maps and network analysis are used mainly for utility management. AM/FM is frequently used in this area.

• Environment and Natural Resources ManagementMedium or small scale maps and overlay techniques in combination with aerial photographs and satellite images are used for management of natural resources and environmental impact analysis.

• Street NetworkLarge or medium scale maps and spatial analysis are used for vehicle routing, locating house and streets etc.

• Planning and EngineeringLarge or medium scale maps and engineering models are used mainly in civil enginerring.

• Land Information SystemLarge scale cadastre maps or land parcel maps and spatial analysis are used for cadastre administration, taxation etc.

Area of GIS Applications

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DEMs and DTMs

• Some definitions…– DEM (Digital Elevation Model)

• set of regularly or irregularly spaced height values• no other information

– DTM (Digital Terrain Model)• set of regularly or irregularly spaced height values• but, with other information about terrain surface• ridge lines, spot heights, troughs, coast/shore lines,

drainage lines, faults, peaks, pits, passes, etc.

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Comparison

Landform Panorama Landform Profile

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LIDAR data (LIght Detection And Ranging)

Horizontal resolution: 2mVertical accuracy: ± 2cm

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Modelling building and topological structures

• Two main approaches:– Digital Elevation Models (DEMs) based on data

sampled on a regular grid (lattice)– Triangular Irregular Networks (TINs) based on

irregular sampled data and Delaunay triangulation

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DEMs and TINs

DEM with sample points TIN based on same sample points

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Advantages/disadvantages• DEMs:

– accept data direct from digital altitude matrices– must be resampled if irregular data used– may miss complex topographic features– may include redundant data in low relief areas– less complex and CPU intensive

• TINs:– accept randomly sampled data without resampling– accept linear features such as contours and breaklines (ridges

and troughs)– accept point features (spot heights and peaks)– vary density of sample points according to terrain complexity

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Derived variables

• Primary use of DTMs is calculation of three main terrain variables: – height

• altitude above datum– aspect

• direction area of terrain is facing– slope

• gradient or angle of terrain

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Calculating slope• Inclination of the land surface measured in

degrees or percent – 3 x 3 cell filter– find best fit tilted plane that minimises squared

difference in height for each cell– determine slope of centre (target) cell

Slope = b2 + c2

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8

9 8

8 7

7 6 5

z = a + bx + cy

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Calculating aspect• Direction the land surface is facing

measured in degrees or nominal classes (N, S, E, W, NE, SE, NW, SW, etc.)– use 3 x 3 filter and best fit tilted plane– determine aspect for target cell

Aspect = tan-1 c / b

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8

9 8

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7 6 5

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Other derived variables

• Many other variables describing terrain features/characteristics– hillshading– profile and plan curvature– feature extraction– etc.

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Examplesheight

slopeaspect

hillshading

plan curvature

Feature extraction

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Problems with DEMs

• Issues worth considering when creating/using DTMs– quality of data used to generate DEM– interpolation technique– give rise to errors in surface such as:

• sloping lakes and rivers flowing uphill• local minima• stepped appearance• etc.

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Example applications

• Visualisation– terrain and other 3D surfaces

• Visibility analysis– intervisibility matrices and viewsheds

• Hydrological modelling– catchment modelling and flow models

• Engineering– cut & fill, profiles, etc.

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Terrain visualisation• Analytical hillshading• Orthographic views

– any azimuth, altitude, view distance/point– surface drapes (point, line and area data)

• Animated ‘fly-through’• What if? modelling

– photorealism– photomontage– CAD

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Examples of hillshading and orthographic projection

Hillshading

DEM

Orthographic projection

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Example surface drape

DEM

Rainfall

Draped image

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Example animated fly-through

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Photorealism

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Photo-realism “what if?” visualisation

Visualisation 1: before felling

Visualisation 2: clear-cut

Visualisation 3: strip felling

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Wind farm – photomontage

before

wire-frame model

after

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DTM Conclusions• Need for third dimensional GIS

– especially in environmental applications– new data models/structures– new opportunities for analysis

• Basic uses and derived variables• Application areas

– visualisation– visibility analysis– etc.

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• Acquisition of DEM data from Satellite Image/Toposheet

• Conduct DEM processing to derive stream, catchment, and drainage point features

• Populate data with required attributes

• Use network analysis and Archydro tools to derive desired metrics

I. Application of GIS for Watershed Management: Basic Steps

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Digital Elevation Model Processing:

DEM is base data to derive the following grids: Flow Direction Flow Accumulation Stream Network Drainage Basins

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•What is stream flow at a given location?

•How many acres of agricultural land occur above a given point?

•To which basins does water flow from a given location?

Network Analysis:

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• What is the dominant land use in a basin?

• How many miles of road occur adjacent to a river?

• How many ha of intensive agriculture occur above a given location?

• What is the relationship between land use and water quality?

• Where are the most vulnerable habitats?

• Where is highest population densities?

Watershed analysis

Local Spatial Data Infrastructure (LSDI) for Watershed Management:

Vital components of watershed management: - Soil and land resource data for planning at micro level - Creation of a multi-temporal database for natural resources. - People's participation - Awareness for farmers, policy makers, users, soil conservationists

and scientists People's participation at micro level Technological Integration: - GIS along with conventional Database - Hydrological and Socio-economic analysis - Technological adoption and Conventional Practices

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III. Virtual reality GIS Applications

• Virtual Reality GIS supports creation, manipulation and exploration of geo-referenced virtual environments

• Applications include 3D simulation for planning with different scenarios

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IV. Real-time GIS Application

With the availability of real-time positioning systems, it is possible to develop GIS that monitor, transmit, record and analyse the movement of mobile agents such as vehicles, people or animals and hazards (telegeomonitoring).

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Real time monitoring of a Tropical Cyclone over west coast of India

Other GIS Application Areas:Health and Anemities planning Market Research, ERP and SAPOperations Management - Distribution and Retail

ServicesSpatial Information Services - Tourist & Tour

OperatorsSpatial Services Management – Defense and

Disaster ManagementSpatial Services Management - Land & Utilities

Planning & Management& Many Others

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Spatial Data InfrastructureConcepts and Components

Spatial Data Infrastructure

(SDI)

SDI as a principle recognizes GIS data as a fundamental infrastructure component for national physical, cultural and economic development, akin to highways, telecommunications networks and educational facilities.

Transportation

Electricity

Telecommunications

Education

SDI

What is an SDI?

What is a Spatial Data Infrastructure (SDI)?

“The SDI provides a basis for spatial data discovery, evaluation, and application for users and providers within all levels of government, the commercial sector, the non-profit sector, academia and by citizens in general.”

--The SDI Cookbook http://www.gsdi.org

Components of a Spatial Data Infrastructure (SDI)

• Policies & Institutional Arrangements (governance, data privacy & security, data sharing, cost recovery)

• People (training, professional development, cooperation, outreach)

• Data (digital base map, thematic, statistical, place names)

• Technology (hardware, software, networks, databases, technical implementation plans)

Here’s an overview of the elements and status of SDI…

Metadata

GEOdata

Clearinghouse (catalog)

Framework

Standards

Partnerships

Metadata

Standards

PartnershipsDiscovery Access

Services

Processing

Framework GEOdata

The first task is to inventory who has what data of what type and quality A standardized form of metadata was published in June 1994 by the US FGDC. An international standard (ISO 19115/19139) now exists and is being adopted by most countries

Metadata

Metadata can apply to data, services, and other resource types

• Provides documentation of existing internal geospatial resources within an organisation (inventory)

• Permits structured search and comparison of held geospatial resources by others (catalog)

• Provides end-users with adequate information to take the resource and apply it in an appropriate context (documentation)

• ISO 19115/TS19139 provide an international standard for metadata and its encoding

Metadata describes data and service resources for order, access, or local use Metadata is used to describe all types of data, emphasis on ‘truth in labeling’

Metadata

Geospatial Data

Services

Special-use thematic layers are built and described as available geospatial dataCommon data layers are being defined in the Framework activity

Metadata

Framework GEOdata

Framework Data Standards

• Eleven abstract data content standards are being promulgated through the ANSI process as American National Standards

• Each theme (layer) is also described as XML/GML Application Schemas that can be served over the Web (OGC Web Feature Services)

Scope: Framework Layers• Elevation• Orthoimagery• Hydrographic Data• Governmental Unit Boundaries• Cadastral• Geodetic Control• Transportation

– Roads n Air – Rail n Marine– Transit

Services

The NSDI includes the services to help discover and interact with data

Metadata

Framework GEOdata

This Discovery Service is provided by a national catalog of geospatial information which can be accessed by a national portal

Services

An important common service in SDI is that of discovering resources through metadata

Discovery Access Processing

Metadata

Framework GEOdata

National Geo-Portal capabilities• Help locate data and services• Support download of data, link to related websites,

and applications for others to access• Support self-organizing communities post and manage

selected content• Share data collection plans and requirements to

support partnerships and collaboration

Metadata Publication Options• Users may contribute metadata one of

three ways:– Enter metadata into a form on the catalog and

they are stored and indexed there– Upload metadata as XML to the catalog from a

GIS or metadata program– Register their existing metadata collection or

service to be harvested into the national catalog

metadatacatalog

Portalmap viewer

metadata

metadata

metadata metadatadata

data

data

data

formentry XML

upload

search

map services

Services

Discovery Access Processing

This may be made via static files on ftp or via web services. These services deliver ‘raw’ geospatial data, not maps.

A second category of services provides standardised access to geospatial information

Metadata

Framework GEOdata

Services

Discovery Access Processing

A third class of services provides additional processing on geospatial information

Metadata

Framework GEOdata

Standardization makes SDI work Standards touch every SDI activity

Discovery

Standards

AccessServices

Processing

Standards include specifications, formal standards, and documented practices

Metadata

Framework GEOdata

Partnerships extend our capabilities

Standards

PartnershipsDiscovery Access

Services

Processing

Metadata

Framework GEOdata

Partnerships are the glue...• Proper governance of the community is essential

through a variety of roles and responsibilities• National government or NGOs should partner

with other levels of government and sectors to promote 2-way coordination

• The government or a foundation may be able to fund agencies with “seed” funding to further existing efforts toward common goals

• Partnerships extend local capabilities in technology, skills, logistics, and data

National Spatial Data

Initiative (U.S.)

Permanent Committee on GIS Infrastructure for

Asia and the Pacific

European Union INSPIRE

Australian Spatial Data

Infrastructure

Growing Number of Regional Initiatives

Qatar National GIS

Oman National GIS

Global Spatial Data

Initiative

Libya Spatial Data Infrastructure

Kuwait SDI

19901980 2000

100 Countries Are Now Developing SDI At Some Level50 Countries Have Signed To Participate in Global Spatial Data InfrastructureThe Community Is Growing Every Year

SDI Network Enables …

Search, Discovery, and Brokering of

access to geospatial resources

DataApplications

Web sitesDocuments

Metadata Plays an Integrating Role

National Spatial Data Infrastructure (NSDI)

• Definition - the technology, policies, standards, human resources, and related activities necessary to acquire, process, distribute, use, maintain, and preserve spatial data

• Part of a nation’s e-Gov strategy

• www.GSDI.org

Framework Data (common)/ Reference Data

• Geoditic network• Administrative Boundaries• Hydrography• Elevation• Roads and Railroads• Cadastre (Land System)• Geographical Names

List of Core Layers

1. Transportation network/Roads/rails/Navigation routes2. Population centres / gridded Population density3. Hydrography / Hydrology / drainage network/ River and lake basins4. Hydrogeology5. Coastlines6. Land-cover/Land-use7. Hypsographic ( elevation contours)8. Bathymetry9. Landmine areas10. Protected area / Restricted areas11. Geology, geomorphology12. Airports/Helipad13. Health facilities

Main NSDI Components

National Information Infrastructure

Spatial Data Infrastructure

National Statistics and

Indicators

ITC National Computing

and Network Infrastructure

Other

Growing recognition that SDI is part of a larger societal issue

What Are the Common Components of NII??

Standards

Policies

Organization

Technology

Many Commonalities and Dependencies

Some SDI examples

• Regional SDI: INSPIRE– INSPIRE: Infrastructure for spatial information in Europe– Adopted on 21 November 2006

• UNSDI: – UN Geographic Information Working Group: Umbrella for UN bodies, in

charge of the UN SDI– Second Administrative-Level Boundaries (SALB) Project

• Global Mapping Initiative:– Core layers at 1:1 million– More than 130 countries are involved

Geographic Information Standards

• ISO/TC 211– Countries

• OpenGIS Consortium– Industry

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Basic data• Administrative units• Transport networks• Hydrography including water catchments• Elevation (including terrestrial elevation, bathymetry and coastline)• Protected sites• Land cover• Cadastral parcels• Ortho-imagery• Coordinate reference systems• Geographical names• Geographical grid systems• Addresses including postal regions

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Level of harmonization of Basic data

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Other data

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Level of harmonization of other data

• Data should be consistent:– Geometrically

• Geo-referencing to allow consistent overlay of data– Semantically

• Definition of spatial objects

Trends in GIS Technology

GIS technology is constantly evolving

• Software and hardware advances• New types of data collection techniques and

devices• New types of applications of technology• GIS is gradually becoming a technology that is

being used in most segments of society, not just natural resources

Integrated raster/vector software• GIS software packages were previously defined as

being a “raster” or “vector” software package– Packages were typically designed for one data structure

and could perhaps dabble in another– ArcInfo workstation and ArcView 3: vector

• This trend has changed as almost all packages now have capabilities in both raster and vector

• Previously, the strong differences between raster and vector data structures prevented integration

• In addition, software manufacturers created their own proprietary data formats that

As software and hardware advances…• Perhaps a fully integrated system, one that offers a

full suite of tools for both raster and vector data will emerge– Vector databases used for image classification– Raster databases used for buffering, overlay, and proximity

operations• This system would allow users to seamlessly use

raster or vector data for GIS operations

Linkage of GIS Databases to other digital data

• Connecting mapped data to other information sources, such as digital photography, video, or text-based information sources

• Allows us to learn more about a mapped feature

Linking GIS data to other information

Figure :A GIS database of urban trees, and an associated hyperlinked picture of a tree (courtesy of Andrew Saunders).

High-resolution databases• Precision forestry and precision agriculture have

become recognized disciplines• Applications seek to use digital technologies for

improving or making more efficient natural resource management activities

• The term “precision agriculture” has been in use for over ten years while precision forestry has recently gained popular usage– The first formal recognition was at the 2001 UW Precision

Forestry Symposium

Precision agriculture applications

• Using GPS as a navigational aid for farm equipment

• Capturing remotely sensed imagery to describe the status of soil properties (to determine the need for fertilizer or pesticides)

• Using digital aerial photographs to record crop plantings and outcomes

Precision forestry applications

• Using electronic distance measuring tools to capture precise spatial positions of forest landscape features

• Capturing precise and timely satellite imagery to assist in monitoring threats to forest health (fire, disease, floods)

• Developing precise, fine-scale DEMs to identify steep forested areas that may be susceptible to landslide activity

Raster data collection appears promising

• Data collection and processing techniques becoming more efficient and affordable

• IKONOS– 1-4m resolution

• Color aerial photography at 1m resolution can be captured and made available to clients within days

IKONOS satellite image at 4 m resolution of

Copper Mountain

located in theColorado Rocky

Mountains(Image courtesy

of GeoEye)

Managing raster data• Raster databases have sometimes been prohibitive to

organizations because of their size– Hard drives are becoming larger and faster but raster data can still

quickly consume space• With proper management, raster data have great potential to

assist organizations that manage large land areas– Keeping land cover information current– Facilitating temporal analysis of land cover change

• The challenge will be in deciding how often to acquire new data and how to integrate new data into existing databases (update questions)– This is a strong contrast from the recent past when organizations often

struggled to create and/or locate data

Distributing GIS capabilities to field offices

• The traditional model of GIS use in organizations was a centralized office that would attempt to provide GIS services and support for all parts of the organization

• Problems with this model:– Accessibility– Timeliness– Communication

• Today’s trend: the distributed model

Distributed GIS capabilities• Makes GIS available to many parts of an organization including

field offices• Many factors have contributed to this model:

– More people graduating from colleges and universities with GIS training

– Less expensive hardware– More user-friendly software

• Benefits include enhanced field office productivity (timeliness, removing communication barriers, and giving employees greater involvement in organizational activities) and a reduction in the centralized GIS office

• This model will likely continue to grow in popularity

Internet data availability• The Internet has been a primary contributor to GIS popularity

– Many public organizations make data available for download– Not long ago, data needed to be physically transported on a storage

device (carried or mailed)• Some organizations still charge for data transfer costs• Some larger databases (raster DOQs) still can’t be efficiently

made available for large land areas– Data compression techniques will likely improve to accommodate

large raster databases

Portable devices for data display and capture

• Handheld and personal data assistants (PDAs) have become increasingly common for collecting forest inventory and landscape data

• GPS receivers can be coupled with hand-held devices to show locations and store measurements– DOQs or DRGs can be displayed in the background to locate features or verify

measurements• These technologies are reducing the use of field data books and the

need to manually record measurements– Has increased the rate at which data can be integrated into a digital database– Reduces the opportunity for human error

• Handheld data collectors are still expensive ($1,000 to 5,000) while PDAs are generally inexpensive ($200-300)

• Still difficult to place complete trust in these instruments for data collection

Standards for the exchange of GIS databases

• The Federal Geographic Data Committee (FGDC) has specified standards for data cataloging– These standards guide the construction of metadata: data about data– All federal agencies are required to comply, most state agencies that

distribute spatial data have also adopted data standards• Private organizations are not bound to data cataloging

standards– Acquisition and modification of GIS data may go undocumented

• ArcInfo coverages and ArcView shapefiles are the most prevalent GIS formats made available by organizations

• DXF files are also popular for schematics and engineering related databases

• Most GIS software allows users to import, or at least view, data in several different formats

Legal issues related to GIS• Privacy, liability, accessibility, and licensing are all hot topics

within GIS at present• Privacy

– Spatial data are being collected about all of us at an ever-increasing rate• Address, family, income, home value, purchasing decisions

– Organizations are purchasing and using this data to help direct advertising

• Mailings, phone calls, e-mails– GIS has become a tool, like it or not, to foster business– As private organizations continue to forge new ground in the collection,

sale, and exchange of spatial data that describe the economic and social behavior of individuals, society will be challenged to maintain privacy

GIS Interoperability

• Interoperability means that software packages get along with one another

• Accomplished through the option of standard terminology, data formats, and software interfaces

• Rapid GIS growth during the 1990s led to numerous incompatible GIS products

Open Geospatial Consortium• Over 340 member organizations, began in 1994• Promotes accessibility to geoprocessing tools and

location-based services• Accomplishments

– Standardized terms: points, lines, and polygons– Created GML (Geography Markup Language), an open

source language for describing spatial data– Standards for how geographic data can be requested and

accessed from Internet servers

GIS Education• GIS capabilities are now essential for natural resource

organizations• No direct accreditation process or organization exists to guide

geospatial technology instruction– ABET provides accreditation for engineering and surveying curriculums

• A need exists to identify the concepts and knowledge necessary for geospatial technology programs in higher-education

• The Geographic Information Science and Technology Body of Knowledge (DiBiase et al. 2006) has attempted to define critical concepts and skills related to GIScience

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Digital Terrain modelling

•Outline– introduction– DEMs and DTMs – derived variables– example applications

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Adding the third dimension

• In high relief areas variables such as altitude, aspect and slope strongly influence both human and physical environments– a 3D data model is therefore essential– use a Digital Terrain Model (DTM)– derive information on:

• height (altitude), aspect and slope (gradient)• watersheds (catchments)• solar radiation and hill shading• cut and fill calculations• etc.