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GIS Data Models Geographic information z Characteristics of Geographic Information yLocation! yvolume yDimensionality xPoint xLine xArea yContinuity.

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Presentation on theme: "GIS Data Models Geographic information z Characteristics of Geographic Information yLocation! yvolume yDimensionality xPoint xLine xArea yContinuity."— Presentation transcript:


2 GIS Data Models

3 Geographic information z Characteristics of Geographic Information yLocation! yvolume yDimensionality xPoint xLine xArea yContinuity xFeature xfield

4 Building complex features zSimple geographic features can be used to build more complex ones. zAreas are made up of lines which are made up of points represented by their coordinates. zAreas = {Lines} = {Points}

5 Properties of Features zsize zdistribution zpattern zcontiguity zneighborhood zshape zscale zorientation.

6 Basic properties of geographic features

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

8 Coming next…. Maps as Numbers

9 GIS Capability zA GIS package should be able to move between ymap projections, ycoordinate systems, ydatums, and yellipsoids.

10 Draw a map of your favorite place in Texas.


12 GIS Data Models

13 Maps as Numbers zGIS requires that both data and maps be represented as numbers. zThe GIS places data into the computer’s memory in a physical data structure (i.e. files and directories). zFiles can be written in binary or as ASCII text. zBinary is faster to read and smaller, ASCII can be read by humans and edited but uses more space.

14 The Data Model zA logical data model is how data are organized for use by the GIS. zGISs have traditionally used either raster or vector for maps.

15 Two approaches to handling spatial data with GIS: zRaster model zVector model yPoints, ylines, ypolygons

16 Features and Maps zA GIS map is a scaled-down digital representation of point, line, area, and volume features. zWhile most GIS systems can handle raster and vector, only one is used for the internal organization of spatial data.

17 Rasters and vectors can be flat files … if they are simple Vector-based line Raster-based line 4753456 623412 4753436 623424 4753462 623478 4753432 623482 4753405 623429 4753401 623508 4753462 623555 4753398 623634 0000000000000000 0001100000100000 1010100001010000 1100100001010000 0000100010001000 0000100010000100 0001000100000010 0010000100000001 0111001000000001 0000111000000000 0000000000000000 Flat File

18 A raster data model uses a grid. zOne grid cell is one unit or holds one attribute. zEvery cell has a value, even if it is “missing.” zA cell can hold a number or an index value standing for an attribute. zA cell has a resolution, given as the cell size in ground units.

19 Raster GIS zRaster Data Model yRows and Columns of Cells (Array) yArea of Cell equals Spatial Resolution yValue for each cell records type of object or condition yCells do not correspond to spatial entities in real world x A road is a group of cells, not a single entity yCells are considered Homogeneous Units

20 Two approaches to handling spatial data with GIS: zRaster model zVector model yPoints, ylines, ypolygons

21 Generic structure for a grid Figure 3.1 Generic structure for a grid. R o w s Columns Grid cell Grid extent Resolution


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


25 More Definitions zResolution - A measure of the accuracy or detail of a graphic display, expressed as dots per inch, pixels per line, lines per millimeter, etc. zSpatial 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.


27 Definitions zMinimum Mapping Unit - The smallest element we can uniquely represent in our data.

28 Sources of Raster Data zSatellite data yLANDSAT ySPOT zScanned aerial photography zDigital Orthophotography zScanned maps and documents

29 From where do we get Raster Data? zSCANNED Aerial photographs yphotographs are NOT raster images but SCANNED images ARE zSCANNED maps zSatellite images



32 From where are the data in a raster cell taken?

33 Why does it matter where the cell data come from? zIt’s hard to tell just by looking at the image!

34 The mixed pixel problem

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

36 Why use Raster? zOverlay Analysis/Overlay Operations zArithmetic Operations yAddition ySubtraction yDivision yMultiplication zLogical (Boolean) Operations yWhere conditions occur or do not occur together xAND, OR, NOT, GT, LT, etc.


38 Raster GIS Applications zIntegrate images to georeferenced data yi.e., parcel deed image linked to parcel centroid zDocument Imaging zNatural Resource applications where: yPositional accuracy relaxed yImagery-oriented

39 Raster Applications zUtility Corridor Siting zEnvironmental Mapping zNatural Communities Mapping zForest resource planning zSpatial data variability decisions zForest inventory zWildlife habitat analysis

40 More Raster Applications zWetlands Vegetation Inventory & Analysis zAgricultural analysis zPlanetary analysis (including lunar) zVector Updating zDigital Terrain Modeling zFlood Control & Emergency Preparedness zCommunication System Engineering

41 Any Technology has Pro’s & Con’s

42 Raster Limitations zAesthetics zData storage requirements zOverlay operations performed on every cell zSparse data sets require as much processing as dense ones

43 RASTER -- summary zA grid or raster maps directly onto a programming computer memory structure called an array. zGrids are poor at representing points, lines and areas, but good at surfaces. zGrids are good only at very localized topology, and weak otherwise. zGrids are a natural for scanned or remotely sensed data. zGrids suffer from the mixed pixel problem. zGrids must often include redundant or missing data. zGrid compression techniques used in GIS are run-length encoding and quad trees.

44 Raster Data Compression Techniques zFull Raster Encoding: Unique value for each cell in every row and column. Data not compressed.

45 zRun-length encoding: In run-length encoding, adjacent cells along a row that have the same value are treated as a group termed a run. Instead of repeatedly storing the same value for each cell, the value is stored once, together with information about the size and location of the run.

46 zValue Point encoding: The cells are assigned position numbers starting in the upper left corner, preceding from left to right and from the top to bottom. The position number for the end of each run is stored in the point column. The value for for each cell in the run is in the value column.

47 zQuadtrees: The quadtree data model provides a more compact raster representation by using a variable-sized grid cell. Instead of dividing an area into cells of one size, finer subdivisions are used in those areas with finer detail.

48  GIS functions: Data input & reporting digitizing scanning kbd. entry format convert.


50 Land Cover Inventory & Mapping za) Urban and built-up land zb) Agricultural land zc) Rangeland zd) Forest land ze) Water z f) Wetland z g) Barren land z h) Tundra z i) Perennial snow or ice Land use/land cover analysis -- Anderson Classification Scheme (Level I) (Anderson, 1976)

51 GIS Data Models

52 Two data formats: zRaster zVector

53 Rasters are faster, but... zPoints and lines in raster format have to move to a cell center. zLines can become fat. Areas may need separately coded edges. zEach cell can be owned by only one feature. zAs data, all cells must be able to hold any cell value. zIt is very difficult to precisely position features in space.

54 Vector GIS Data Model zPrecisely position features in space yPoints, Nodes, vertex, single X,Y coordinate pair yLines, Arcs, series of X,Y coordinate pairs yArea, Polygons, area as a closed loop of X,Y coordinate pairs

55 Areas are lines are points are coordinates

56 The Vector Model zA vector data model uses points stored by their real (earth) coordinates and so requires a precise coordinate system. xGeographic Coordinate System Latitude/Longitude xCartesian Coordinate Systems X,Y Coordinate system State Plane UTM (Universal Transverse Mercator) zLines and areas are built from sequences of points in order. zLines have a direction to the ordering of the points. zPolygons can be built from points or lines. zVectors can store information about topology.

57 The quad-tree structure Figure 3.9 The quad-tree structure. Reference to code 210. 210 01 23 01 23 0 3 quadrant number 2 1

58 Raster/Vector Comparison

59 VECTOR zAt first, GISs used vector data and cartographic spaghetti structures. yCollection of coordinate strings with no structure yCartesian coordinates stored in data structure yNo spatial relationships stored yInefficient data storage technique zVector data evolved the arc/node model in the 1960s. zIn the arc/node model, an area consist of lines and a line consists of points. zPoints, lines, and areas can each be stored in their own files, with links between them.

60 Arc/node map data structure with files Figure 3.4Arc/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 2 3 4 5 6 7 8 9 10 11 12 13 1 x y 2 x y 3 x y 4 x y 5 x y 6 x y 7 x y 8 x y 9 x y 10 x y 11 x y 12 x y 13 x y P o i n t s F i l e 1 2 2 1,8,9,10,11,12,13,7

61 zThe topological vector model uses the line (arc) as a basic unit. Areas (polygons) are built up from arcs. zThe endpoint of a line (arc) is called a node. Arc junctions are only at nodes. zStored with the arc is the topology (i.e. the connecting arcs and left and right polygons).

62 Vectors zTIN must be used to represent volumes. zVector can represent point, line, and area features very accurately. zVectors work well with pen and light-plotting devices and tablet digitizers. zVectors are not good at continuous coverages or plotters that fill areas.

63 Vector Data Model "Primitives" zPoint: single X,Y coordinate pair zLine: series of X,Y coordinate pairs zPolygon: area as a closed loop of X,Y coordinate pairs


65 Vector GIS Relies on a precise coordinate system zGeographic Coordinate System yLatitude/Longitude zCartesian Coordinate Systems yX,Y Coordinate system yState Plane yUTM (Universal Transverse Mercator)

66 Topological Model zTopology: mathematical method to define spatial relationships zArc-node data model yArc: a series of points that start and end at a node yNode: an intersection point where two or more arcs meet

67 Topological Data Spatial Operations zContiguity: spatial relationship of adjacency yi.e., stand of coniferous trees adjacent to deciduous trees zConnectivity: interconnected pathways or networks yi.e., street and trail networks, stream networks

68 Basic arc topology n1 n2 1 2 3 A B ArcFromToPLPRn1xn1yn2xn2y 1n1n2ABxyxy Topological Arcs File Figure 3.5 A topological structure for the arcs.

69 TOPOLOGY zTopological data structures dominate GIS software. zTopology allows automated error detection and elimination. zRarely are maps topologically clean when digitized or imported. zA GIS has to be able to build topology from unconnected arcs. zNodes that are close together are snapped. zSlivers due to double digitizing and overlay are eliminated.

70 Slivers Sliver

71 Unsnapped node

72 The bounding rectangle (xmax, ymax) (xmin, ymin)

73 Topology Matters zThe tolerances controlling snapping, elimination, and merging must be considered carefully, because they can move features. zComplete topology makes map overlay feasible. zTopology allows many GIS operations to be done without accessing the point files.

74 Vectors and 3D zVolumes (surfaces) are structured with the Triangulated Irregular Network model, including edge or triangle topology. zTINs use an optimal Delaunay triangulation of a set of irregularly distributed points. z TINs are popular in CAD and surveying packages.

75 TIN: Triangulated Irregular Network zWay to handle field data with the vector data structure. zCommon in some GISs and most AM/FM packages. zMore efficient than a grid.

76 Sources of Vector Data zRASTER-VECTOR conversions from scanned images zPre-existing digital data from disks or internet zDIGITIZING


78 Vector to raster to vector conversion


80 Comparison: Raster and Vector


82 FORMATS zMost GIS systems can import different data formats, or use utility programs to convert them. zData formats can be industry standard, commonly accepted or standard.

83 Vector Data Formats zVector formats are either page definition languages or preserve ground coordinates. zPage languages are HPGL, PostScript, and Autocad DXF. zTrue vector GIS data formats are DLG and TIGER, which has topology.

84 The TIGER data structure 156 157 159 21 22 23 13 17 18 19 Lake Drive First St. Second St. Third St. Avenue A A v e n u e B A v e n u e C A v e n u e D 158 86 87 88 89 90 91 85 Two cell One cell Zero cell Map 3 Addresses on block Landmark Zero cells One cells Two cells Nodes 13,17,18,19, 21,22,23,156,157, 158,159 1,2,3,4,5,6,7,8, 9,10,11,12,13,14, 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 15,16,17,18 Lake, Blocks 86, 87, 88, 89, 90, 91 Addresses (x,y) values Files

85 Raster Data Formats zMost raster formats are digital image formats. zMost GISs accept TIF, GIF, JPEG or encapsulated PostScript, which are not georeferenced. zDEMs are true raster data formats.

86 DEMs and UTM (7.5 minute 30m)

87 EXCHANGE zMost GISs use many formats and one data structure. zIf a GIS supports many data structures, changing structures becomes the user’s responsibility. zChanging vector to raster is easy; raster to vector is hard. zData also are often exchanged or transferred between different GIS packages and computer systems. zThe history of GIS data exchange is chaotic and has been wasteful.

88 Vector to raster exchange errors

89 Transfer Standards

90 GIS Data Exchange zData exchange by translation (export and import) can lead to significant errors in attributes and in geometry. zIn the United States, the SDTS was evolved to facilitate data transfer. zSDTS became a federal standard (FIPS 173) in 1992. zSDTS contains a terminology, a set of references, a list of features, a transfer mechanism, and an accuracy standard. zBoth DLG and TIGER data are available in SDTS format. zOther standards efforts are DIGEST, DX-90, the Tri-Service Spatial Data Standards, and many other international standards. zEfficient data exchange is important for the future of GIS.

91 Attribute data zAttribute data are stored logically in flat files. zA flat file is a matrix of numbers and values stored in rows and columns, like a spreadsheet. zBoth logical and physical data models have evolved over time. zDBMSs use many different methods to store and manage flat files in physical files.

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