GIS Data Models

Geographic information

Characteristics of Geographic Information Location! volume Dimensionality

PointLineArea

ContinuityFeaturefield

Building complex features

Simple geographic features can be used to build more complex ones.

Areas are made up of lines which are made up of points represented by their coordinates.

Areas = {Lines} = {Points}

Properties of Features

size distributionpatterncontiguityneighborhoodshapescaleorientation.

Basic properties of geographic features

GIS Analysis

Much of GIS analysis and description consists of investigating the properties of geographic features and determining the relationships between them.

GIS Capability

A GIS package should be able to move between map projections, coordinate systems, datums, and ellipsoids.

Draw a map of your favorite place in Texas.

GIS Data Models

Maps as Numbers

GIS requires that both data and maps be represented as numbers.

The GIS places data into the computer’s memory in a physical data structure (i.e. files and directories).

Files can be written in binary or as ASCII text.

Binary is faster to read and smaller, ASCII can be read by humans and edited but uses more space.

The Data Model

A logical data model is how data are organized for use by the GIS.

GISs have traditionally used either raster or vector for maps.

Two approaches to handling spatial data with GIS:

Raster model Vector model

Points, lines, polygons

Features and Maps

A GIS map is a scaled-down digital representation of point, line, area, and volume features.

While most GIS systems can handle raster and vector, only one is used for the internal organization of spatial data.

Rasters and vectors can be flat files … if they are simple

Vector-based line

Raster-based line

4753456 6234124753436 6234244753462 6234784753432 6234824753405 6234294753401 6235084753462 6235554753398 623634

00000000000000000001100000100000101010000101000011001000010100000000100010001000000010001000010000010001000000100010000100000001011100100000000100001110000000000000000000000000

Flat File

Flat File

A raster data model uses a grid.

One grid cell is one unit or holds one attribute. Every cell has a value, even if it is “missing.” A cell can hold a number or an index value

standing for an attribute. A cell has a resolution, given as the cell size in

ground units.

Raster GIS

Raster Data Model Rows and Columns of Cells (Array) Area of Cell equals Spatial Resolution Value for each cell records type of object or

condition Cells do not correspond to spatial entities in

real world A road is a group of cells, not a single entity

Cells are considered Homogeneous Units

Two approaches to handling spatial data with GIS:

Raster model Vector model

Points, lines, polygons

Generic structure for a grid

Figure 3.1 Generic structure for a grid.

Row

s

Columns

Gridcell

Grid extent

Resolution

Definitions

Raster - A format for storing, processing, and displaying graphic data in which graphic images are stored as values for uniform grid cells or pixels.

Pixels - Abbreviation for picture element, the smallest indivisible element that makes up an image. In raster processing, data is represented spatially on a matrix of grid cells, called pixels, which are assigned values for image characteristics or attributes.

More Definitions

Resolution - A measure of the accuracy or detail of a graphic display, expressed as dots per inch, pixels per line, lines per millimeter, etc.

Spatial Resolution - The accuracy associated with the capture of ground information as reproduced in a digital format or graphic display. For example, 10-foot pixels vs. 100-foot pixels.

Definitions

Minimum Mapping Unit - The smallest element we can uniquely represent in our data.

Sources of Raster Data

Satellite data LANDSAT SPOT

Scanned aerial photography Digital Orthophotography Scanned maps and documents

From where do we get Raster Data?

SCANNED Aerial photographs photographs are NOT raster images but

SCANNED images ARESCANNED mapsSatellite images

From where are the data in a raster cell taken?

Why does it matter where the cell data come from?

It’s hard to tell just by looking at the image!

The mixed pixel problem

W GW

W W G

W W G

W GG

W W G

W G G

W GE

W E G

E E G

Water dominates Winner takes all Edges separate

Grids and missing data

Figure 3.8 GIS data layer as a grid with a large section of “missing data,” in thiscase, the zeros in the ocean off of New York and New Jersey.

Why use Raster?Overlay Analysis/Overlay OperationsArithmetic Operations

Addition Subtraction Division Multiplication

Logical (Boolean) Operations Where conditions occur or do not occur

together AND, OR, NOT, GT, LT, etc.

Raster GIS Applications

Integrate images to georeferenced data i.e., parcel deed image linked to parcel

centroid Document Imaging Natural Resource applications where:

Positional accuracy relaxed Imagery-oriented

Raster Applications

Utility Corridor Siting Environmental Mapping Natural Communities Mapping Forest resource planning Spatial data variability decisions Forest inventory Wildlife habitat analysis

More Raster Applications

Wetlands Vegetation Inventory & Analysis

Agricultural analysis Planetary analysis (including lunar) Vector Updating Digital Terrain Modeling Flood Control & Emergency Preparedness Communication System Engineering

Any Technology has Pro’s & Con’s

Raster Limitations

Aesthetics Data storage requirements Overlay operations performed on

every cell Sparse data sets require as much

processing as dense ones

RASTER -- summary

A grid or raster maps directly onto a programming computer memory structure called an array.

Grids are poor at representing points, lines and areas, but good at surfaces.

Grids are good only at very localized topology, and weak otherwise.

Grids are a natural for scanned or remotely sensed data.

Grids suffer from the mixed pixel problem. Grids must often include redundant or missing data. Grid compression techniques used in GIS are run-

length encoding and quad trees.

GIS Data Models

Rasters are faster, but...

Points and lines in raster format have to move to a cell center.

Lines can become fat. Areas may need separately coded edges.

Each cell can be owned by only one feature. As data, all cells must be able to hold any cell

value. It is very difficult to precisely position features

in space.

Vector GIS Data Model

Precisely position features in space Points, Nodes, vertex, single X,Y

coordinate pair Lines, Arcs, series of X,Y coordinate

pairs Area, Polygons, area as a closed loop of

X,Y coordinate pairs

Areas are lines are points are coordinates

The Vector Model

A vector data model uses points stored by their real (earth) coordinates and so requires a precise coordinate system.

Geographic Coordinate System• Latitude/Longitude

Cartesian Coordinate Systems• X,Y Coordinate system • State Plane • UTM (Universal Transverse Mercator)

Lines and areas are built from sequences of points in order. Lines have a direction to the ordering of the points. Polygons can be built from points or lines.

Vectors can store information about topology.

Raster/Vector Comparison

VECTOR

At first, GISs used vector data and cartographic spaghetti structures. Collection of coordinate strings with no structure Cartesian coordinates stored in data structure No spatial relationships stored Inefficient data storage technique

Vector data evolved the arc/node model in the 1960s.

In the arc/node model, an area consist of lines and a line consists of points.

Points, lines, and areas can each be stored in their own files, with links between them.

Arc/node map data structure with files

Figure 3.4 Arc/Node Map Data Structure with Files.

1 1,2,3,4,5,6,7

Arcs File

POLYGON “A”

A: 1,2, Area, Attributes

File of Arcs by Polygon

1

23

4

5

6

7

8

9

10

1112

13 1 x y2 x y3 x y4 x y5 x y6 x y7 x y8 x y9 x y10 x y11 x y12 x y13 x y

Po

ints

Fil

e

1

2

2 1,8,9,10,11,12,13,7

The topological vector model uses the line (arc) as a basic unit. Areas (polygons) are built up from arcs.

The endpoint of a line (arc) is called a node. Arc junctions are only at nodes.

Stored with the arc is the topology (i.e. the connecting arcs and left and right polygons).

Vectors

TIN must be used to represent volumes. Vector can represent point, line, and area

features very accurately. Vectors work well with pen and light-plotting

devices and tablet digitizers. Vectors are not good at continuous coverages or

plotters that fill areas.

Topological Model

Topology: mathematical method to define spatial relationships

Arc-node data model Arc: a series of points that start and end

at a node Node: an intersection point where two

or more arcs meet

Topological Data Spatial Operations

Contiguity: spatial relationship of adjacency i.e., stand of coniferous trees adjacent

to deciduous trees Connectivity: interconnected

pathways or networks i.e., street and trail networks, stream

networks

Basic arc topology

n1

n2

123 A

B

Arc From To PL PR n1x n1y n2x n2y1 n1 n2 A B x y x y

Topological Arcs File

Figure 3.5 A topological structure for the arcs.

TOPOLOGY

Topological data structures dominate GIS software. Topology allows automated error detection and

elimination. Rarely are maps topologically clean when digitized

or imported. A GIS has to be able to build topology from

unconnected arcs. Nodes that are close together are snapped. Slivers due to double digitizing and overlay are

eliminated.

Slivers

Sliver

Unsnapped node

Topology Matters

The tolerances controlling snapping, elimination, and merging must be considered carefully, because they can move features.

Complete topology makes map overlay feasible.

Topology allows many GIS operations to be done without accessing the point files.

Vectors and 3D

Volumes (surfaces) are structured with the Triangulated Irregular Network model, including edge or triangle topology.

TINs use an optimal Delaunay triangulation of a set of irregularly distributed points.

TINs are popular in CAD and surveying packages.

TIN: Triangulated Irregular Network

Way to handle field data with the vector data structure.

Common in some GISs and most AM/FM packages.

More efficient than a grid.

Sources of Vector Data

RASTER-VECTOR conversions from scanned images

Pre-existing digital data from disks or internet

DIGITIZING

Vector to raster to vector conversion

Comparison: Raster and Vector

FORMATS

Most GIS systems can import different data formats, or use utility programs to convert them.

Data formats can be industry standard, commonly accepted or standard.

Vector Data Formats

Vector formats are either page definition languages or preserve ground coordinates.

Page languages are HPGL, PostScript, and Autocad DXF.

True vector GIS data formats are DLG and TIGER, which has topology.

Raster Data Formats

Most raster formats are digital image formats.

Most GISs accept TIF, GIF, JPEG or encapsulated PostScript, which are not georeferenced.

DEMs are true raster data formats.

EXCHANGE

Most GISs use many formats and one data structure. If a GIS supports many data structures, changing structures

becomes the user’s responsibility. Changing vector to raster is easy; raster to vector is hard. Data also are often exchanged or transferred between

different GIS packages and computer systems. The history of GIS data exchange is chaotic and has been

wasteful.

Vector to raster exchange errors

Transfer Standards

GIS Data Exchange

Data exchange by translation (export and import) can lead to significant errors in attributes and in geometry.

In the United States, the SDTS was evolved to facilitate data transfer.

SDTS became a federal standard (FIPS 173) in 1992. SDTS contains a terminology, a set of references, a list of

features, a transfer mechanism, and an accuracy standard. Both DLG and TIGER data are available in SDTS format. Other standards efforts are DIGEST, DX-90, the Tri-Service Spatial

Data Standards, and many other international standards. Efficient data exchange is important for the future of GIS.

Attribute data

Attribute data are stored logically in flat files. A flat file is a matrix of numbers and values

stored in rows and columns, like a spreadsheet. Both logical and physical data models have

evolved over time. DBMSs use many different methods to store and

manage flat files in physical files.