2 GIS and the Levels of Science Description:Using GIS to create descriptive models of the world--representations of reality as it exists.Analysis:Using GIS to answer a question or test an hypothesis.Often involves creating a new conceptual output layer, (or table or chart), the values of which are some transformation of the values in the descriptive input layer.--e.g. buffer or slope or aspect layersPrediction:Using GIS capabilities to create a predictive model of a real world process, that is, a model capable of reproducing processes and/or making predictions or projections as to how the world might appear e.g. flood models, fire spread models, urban growth models
3 The Analysis Challenge Recognizing which generic GIS analytic capability (or combination) can be used to solve your problem:meet an operational needanswer a question posed by your boss or your boardaddress a scientific issue and/or test a hypothesisSend mailings to property owners potentially affected by a proposed change in zoningDetermine if a crime occurred within a school’s “drug free zone”Determine the acreage of agricultural, residential, commercial and industrial land which will be lost by construction of new highway corridorDetermine the proportion of a region covered by igneous extrusionsDo Magnitude 4 or greater sub-oceanic earthquakes occur closer to the Pacific coast of South America than of North America?Are gas stations or fast food joints closer to freeways?
4 Availability of Capabilities in GIS Software Descriptive Focus: Basic Desktop GIS packagesData editing, description and basic analysisArcViewMapinfoGeomediaAnalytic Focus: Advanced Professional GIS systemsMore sophisticated data editing plus more advanced analysisARC/INFO, MapInfo Pro, etc.Provided through extra cost Extensions or professional versions of desktop packagesPrediction: Specialized modeling and simulationvia scripting/programming within GISVB and ArcObjects in ArcGISAvenue scripts in ArcView 3.2AMLs in Workstation ARC/INFO (v. 7)Write your own or download from ESRI Web sitevia specialized packages and/or GISs3-D Scientific Visualization packagestransportation planning packages e.g TransCADERDAS, ER Mapper or similar package for rasterCapabilities move‘down the chain’over time.In earlier generation GIS systems, use of advanced applications often required learning another package with a different user interface and operating system (usually UNIX).
5 Description and Basic Analysis (Table of Contents) Spatial OperationsVectorspatial measurementCentrographic statisticsbuffer analysisspatial aggregationredistrictingregionalizationclassificationSpatial overlays and joinsRasterneighborhood analysis/spatial filteringRaster modelingAttribute Operationsrecord selectiontabular via SQL‘information clicking’ with cursorvariable recodingrecord aggregationgeneral statistical analysistable relates and joins
6 Spatial operations: Spatial Measurement Spatial measurements:distance measuresbetween pointsfrom point or raster to polygon or zone boundarybetween polygon centroidspolygon areapolygon perimeterpolygon shapevolume calculatione.g. for earth moving, reservoirsdirection determinatione.g. for smoke plumesComments:Cartesian distance via PythagorusUsed for projected data by ArcMap measure toolsSpherical distance via spherical coordinatesCos d = (sin a sin b) + (cos a cos b cos P)where: d = arc distancea = Latitude of Ab = Latitude of BP = degrees of long. A to BUsed for unprojected data by ArcMap measure toolspossible distance metrics:straight line/airlinecity block/manhattan metricdistance thru networktime/friction thru networkshape often measured by:Projection affects values!!!ArcGIS geodatabases contain automatic variables:shape.length: line length orpolygon perimetershape.area: polygon areaAutomatically updated after editing.For shapefiles, these must be calculated e.g. by opening attribute table and applying Calculate Geometry to a column (AV 9.2)perimeterarea x 3.54= 1.0 for circle= 1.13 for squareLarge for complex shapeDistances depend on projection.Perimeter to area ratio differs
7 Spatial operations: Spatial Measurement Area and Perimeter measures are automatically maintained in the attributes table for a Geodatabase or coverage. For a shapefile, you need to apply Calculate Geometry to an appropriate column in the attribute table (or convert to a geodatabase) .The shape index can be calculated from the area and perimeter measurements. (Note: shapefile and shape index are unrelated)
8 Spatial Measurement: Calculating the Area of a Polygon 1052,37,77,36,24,7Area=(2 x 4)/2=4Area=(3 x 4)=12Area=(5 x 1)/2=2.5A-BC=105510510-=10The actual algorithm used obtains the area of A by calculating the areas of B and C, and then subtracting.The actual formulae used is as follows:The area of the above polygon is 18.5, based on dividing it into rectangles and triangles. However, this is not practical for a complex polygon.Area of triangle =(base x height)/2Its implementation in Excel is shown below.
9 Spatial Operations: Centrographic Statistics Basic descriptors for spatial point distributionsTwo dimensional (spatial) equivalents of standard descriptive statistics (mean, standard deviation) for a single-variable distributionMeasures of Centrality (equivalent to mean)Mean Center and CentroidMeasures of Dispersion (equivalent to standard deviation or variance)Standard DistanceStandard Deviational EllipseCan be applied to polygons by first obtaining the centroid of each polygonBest used in a comparative context to compare one distribution (say in 1990, or for males) with another (say in 2000, or for females)
10 Centroid and Mean Center balancing point for a spatial distributionanalogous to the meansingle point representation for a polygon (centroid)single point summary for a point distribution (mean center)can be weighted by ‘magnitude’ at each point (analogous to weighted mean)minimizes squared distances to other points, thus ‘distant’ points have bigger influence than close points ( Oregon births more impact than Kansas births!)is not the point of “minimum aggregate travel”--this would minimize distances (not their square) and can only be identified by approximation.useful forsummarizing change over time in a distribution (e.g US pop. centroid every 10 years)placing labels for polygonsfor weird-shaped polygons, centroid may not lie within polygoncentroid outsidepolygonNote: many ArcView applications calculate only a “psuedo” centroid: the coordinates of the bounding box (the extent) of the polygonCan be implemented via:ArcToolbox>Spatial Statistics Tools>Measuring Geographic Distributions>Mean Center
11 Calculating the centroid of a polygon or the mean center of a set of points. 1052,37,77,36,24,7(same example data as for area of polygon)1052,37,77,36,24,7Calculating the weighted mean center. Note how it is pulled toward the high weight point.
12 Median Center:Intersection of a north/south and an east/west line drawn so half of population lives above and half below the e/w line, and half lives to the left and half to the right of the n/s line.Same as “point of minimum aggregate travel” the location that would minimize travel distance if we brought all US residents straight to one location.Mean Center:Balancing point of a weightless map, if equal weights placed on it at the residence of every person on census day.Note: minimizes squared distances. The point is considerable west of the median center because of the impact of “squared distance” to “distant” populations on west coastFor a fascinating discussion of the effect of population projection see: E. Aboufadel & D. Austin, A new method for calculating the mean center of population center of the US Professional Geographer, February 2006, ppSource: US Statistical Abstract 2003
13 Standard Distance Deviation single unit measure of the spread or dispersion of a distribution. Is the spatial equivalent of standard deviation for a single variableEquivalent to the standard deviation of the distance of each point from the mean centerGiven by:which by Pythagoras reduces to:---the square root of the average squared distance---essentially the average distance of points from the centerWe can also weight each point and calculate weighted standard distance (analogous to weighted mean center.)
14 Standard Distance Deviation Example 1052,37,77,36,24,7Circle with radii=SDD=2.9
15 Standard Deviational Ellipse: concept Standard distance deviation is a good single measure of the dispersion of the incidents around the mean center, but it does not capture any directional biasdoesn’t capture the shape of the distribution.The standard deviation ellipse gives dispersion in two dimensionsDefined by 3 parametersAngle of rotationDispersion along major axisDispersion along minor axisThe major axis defines the direction of maximum spread of the distributionThe minor axis is perpendicular to it and defines the minimum spread
16 Standard Deviational Ellipse: example There appears to be no major difference between the location of the software and telecommunications industry in North Texas.For formulae for its calculation, seeLee and Wong Statistical Analysis with ArcView GIS pp (1st ed.), pp (2nd ed.)
17 Spatial Operations: buffer zones region within ‘x’ distance unitsbuffer any object: point, line or polygonuse multiple buffers at progressively greater distances to show gradationmay define a ‘friction’ or ‘cost’ layer so that spread is not linear with distanceImplement in Arcview 3.2 with Theme/Create buffers in ArcGIS 8 with ArcToolbox>Analysis Tools>Bufferpolygon bufferExamples200 foot buffer around property where zoning change requested100 ft buffer from stream center line limiting development3 mile zone beyond city boundary showing ETJ (extra territorial jurisdiction)use to define (or exclude) areas as options (e.g for retail site) or for further analysisin conjunction with ‘friction layer’, simulate spread of firepointbufferslinebufferNote: only one layer is involved, but the buffer can be output as a new layer
18 Spatial Operations: spatial aggregation Grouping/combining polygons—is applied to one polygon layer only.districting/redistrictinggrouping contiguous polygons into districtsoriginal polygons preservedRegionalization (or dissolving)grouping polygons into contiguous regionsoriginal polygon boundaries dissolvedclassificationgrouping polygons into non-contiguous regionsoriginal boundaries usually dissolvedusually ‘formal’ groupingsCriteria may be:formal (based on in situ characteristics) e.g. city neighborhoodsfunctional (based on flows or links): e.g. commuting zonesGroupings may be:contiguousnon-contiguousBoundaries for original polygons:may be preservedmay be removed (called dissolving)Examples:elementary school zones to high school attendance zones (functional districting)election precincts (or city blocks) into legislative districts (formal districting)creating police precincts (funct. reg.)creating city neighborhood map (form. reg.)grouping census tracts into market segments--yuppies, nerds, etc (class.)creating soils or zoning map (class)Implement in ArcView 9 thru ArcToolbox>Generalization>Dissolve
19 Districting: elementary school attendance zones grouped to form junior high zones.Regionalization: census tracts grouped into neighborhoodsClassification: cities categorized as central city or suburbssoils classified as igneous, sedimentary, metamorphic
20 Spatial Operations: Spatial Matching: Spatial Joins and Overlays Examplesassign environmental samples (points) to census tracts to estimate exposure per capita (point in polygon)identify tracts traversed by freeway for study of neighborhood blight (polygon on lines)integrate census data by block with sales data by zip code (polygon on polygon)Clip US roads coverage to just cover Texas (polygon on line)Join capital city layer to all city layer to calculate distance to nearest state capital (point on point)combine two (or more) layers to:select features in one layer, &/orcreate a new layerused to integrate data having different spatial properties (point v. polygon), or different boundaries (e.g. zip codes and census tracts)can overlay polygons on:points (point in polygon)lines (line on polygon)other polygons (polygon on polygon)many different Boolean logic combinations possibleUnion (A or B)Intersection (A and B)A and not B ; not (A and B)can overlay points on:Points, which finds & calculates distance to nearest point in other themeLines, which calculates distance to nearest line
21 Example: Spatial Matching: Clipping and Erasing (sometimes referred to as spatial extraction)CLIP - extracts those features from an input coverage that overlap with a clip coverage. This is the most frequently used polygon overlay command to extract a portion of a coverage to create a new coverage.ERASE - erases the input coverage features that overlap with the erase coverage polygons.
22 Example: Spatial Matching via Polygon-on-Polygon Overlay: Union DrainageBasinsThe two layers (land use & drainage basins) do not have common boundaries. GIS creates combined layer with all possible combinations, permitting calculation of land use by drainage basin.a.b.c.aGaAbAbGcAcGLand UseA.G.AtlanticGulfCombined layerNote: the definition of Union in GIS is a little different from that in mathematical set theory. In set theory, the union contains everything that belongs to any input set, but original set membership is lost. In a GIS union, all original set memberships are explicitly retained.In set theory terms, the outcomeof the above would simply be:Another exampleGIS Union1Set Theory Union23
23 Implementing Spatial Matching in ArcGIS 9 Available in three placesvia Selection/Select by Locationthis selects features of one layer(s) which relate in some specified spatial manner to the features in another layerif desired, selected features may be saved later to a new theme via Data/Export DataIndividual features are not themselves modifiedvia Spatial Join (right click layer in T of C, select Join/Joins and Relates, then click down arrow in first line of Join Data window---see Joining Data in Help for details)Use for: points in polygonlines in polygonpoints on lines (to calculate distance to nearest line)points on points (to calculate distance to “nearest neighbor” point)operate on tables and normally creates a new table with additional variables, but again does not modify spatial features themselvesvia ArcToolboxGenerally these tools modify geographic feature, thus they create a new layer (e.g. shape file)Tools are organized into multiple categoriesArcToolbox ExamplesDissolve features based on an attributeCombine contiguous polygons and remove common borderArcToolbox>Generalization>DissolveClip one layer based on anotherArcToolbox>Analysis Tools>Extract>ClipUse one theme to limit features in another theme (e.g. limit a Texas road theme to Dallas county only)Intersect two layers (extent limited to common area)ArcToolbox>Analysis Tools>Overlay>IntersectUse for polygon on polygon overlayUnion two layers (covers full extent of both layers)
24 Spatial Operations: neighborhood analysis/spatial filtering spatial convolution or filterapplied to one raster layervalue of each cell replaced by some function of the values of itself and the cells (or polygons) surrounding itcan use ‘neighborhood’ or ‘window’ of any size3x3 cells (8-connected)5x5, 7x7, etc.differentially weight the cells to produce different effectskernel for 3x3 mean filter:1/9 1/9 1/9low frequency ( low pass) filter:mean filtercell replaced by the mean for neighborhoodequivalent to weighting (mutiplying) each cell by 1/9 = .11 (in 3x3 case)smooths the datause larger window for greater smoothingmedian filteruse median (middle value) instead of meansmoothing, especially if data has extreme value outliersweights mustsum to 1.0
25 Spatial Operations: spatial filtering -- high pass filter high frequency (high pass) filternegative weight filterexagerates rather than smooths local detailused for edge detectionstandard deviation filter (texture transform)calculate standard deviation of neighborhood raster valueshigh SD=high texture/variabilitylow SD=low texture/variabilityagain used for edge detectionneighorhoods spanning border have large SD ‘cos of variabilitycell values (vi ) oneach side of edge25filtered values forhighlighted pixel1(5)(9)+5(5)(-1)+3(2)(-1) = 141(2)(9)+5(2)(-1)+3(5)(-1) = -7kernel for example (wi)1(2)(9)+8(2)(-1) = 21(5)(9)+8(5)(-1) = 5fi.vi.wi
26 Spatial Operations: raster–based modelling Relating multiple rastersProcesses may be:Local: one cell onlyNeighborhood: cells relating to each other in a defined mannerZonal: cells in a given sectionGlobal: all cellsArcGIS implementation:All raster analyses require either the Spatial Analyst or 3-D Analyst extensionsBase ArcView can do no more than display an image (raster) data setSuitability modelingDiffusion ModelingConnectivity Modeling11forsaleSiteoptions2soilslope1111132System attime t+1IncidencematrixProbabilitymaskInitialStateConnectivitymatrixResultantState
27 Attribute Operations: record selection or extraction --features selected on the map are identified in the table (and visa versa)Select by Attribute (tabular)Independent selection by clicking table rows:Open Attribute Table & click on grey selection box at start of row (hold ctrl for multiple rows)Create SQL queryuse Selection/Select by Attributeuse table Relates /Joins to select specific dataSelect by GraphicManually, one point at a timeuse Select Features toolwithin a rectangle or an irregular polygonuse Selection/Select by Graphicwithin a radius (circle) around a point or pointsuse Selection/Select by Location (are wthin distance)Select by LocationBy using another layerUse Selection/Select by Location(same as Spatial Matching discussed previously)Hot LinkClick on map to ‘hot link’ to pictures, graphs, or other mapsOutputs may be:Simultaneously highlighted records in table, and features on mapNew tables and/or map layersExamplesUse SQL query to select all zip codes with median incomes above $50,000 (tabular)identify zip codes within 5 mile radius of several potential store sites and sum household income (graphic)show houses for sale on map, and click to obtain picture and additional data on a selected house (hot link)
28 Attribute Operations: statistical analysis on one or more columns in table univariate (one variable or column)central tendency: mean, median, modedispersion: standard deviation, min, maxTo obtain these statistics in ArcGIS:Right click in T of C and select Open attribute tableRight click on column heading and select Statisticsbivariate (relating two variables or columns)interval and nominal scale variables: sum or mean by categoryaverage crop yield by silt-sand-clay soil typesTo implement in ArcGIS, proceed as above but use Summarizetwo interval scale variables: correlation coefficientsincome by educationArcScripts are available for this on ESRI web site (or use Excel!)multivariate (more than two variables)usually requires external statistical package such as SAS, SPSS, STATA or S-PLUS
29 Attribute Operations: variable recoding establishing/modifying number of classes and/or their boundaries for continuous variable. Options for ArcGISnatural breaks (default) (finds inherent inherent groups via Jenks optimization which minimizes the variances within each of the classes).quantile (classes contain equal number of records-- or equal area under the frequency distribution)equal interval (user selects # of classes)(equal width classes on variable)Defined interval (user selects width of classes)standard deviation(categories based on 1,2, etc, SDsabove/below mean)Manual (user defined)whole numbers (e.g. 2,000)meaningful to phenomena (e.g zero, 32o)aggregating categories on a nominal (or ordinal) variablepine and fir into evergreenNo change in number of records (observations).Implement in ArcGIS via:Right click in T of C, select Properties, then Symbology tab-11-2234%14%.68-.6823%25%(assumes a Normal distribution)Equal area %Equal interval %Standard DeviationEqual interval scoreEqual area score
30 Attribute Operations: record aggregation combining two or more records into one, based on common values on a key variablethe attribute equivalent of regionalization or classificationequivalent of PROC SUMMARY in SASinterval scale variables can be aggregated using mean, sum, max, min, standard deviation, etc. as appropriateordinal and nominal require special considerationexample: aggregate county data to states, or county to CMSARecord count decreases (e.g. from 12 to 2)sumsumre-calc.countaverageofmedians!Type of processing:
31 Attribute Operations: Joining and Relating Tables associating spatial layer to non-spatial table Join: one to one, or one to many, relationship appends attributesAssociate table of country capitals with country layer: only one capital for each country (one to one)Associate country layer with type of government: one gov. type assigned to many countries--but each country has only one gov. type (one to many)
32 Single most common error in GIS Analysis --intending a one to one join of attribute to spatial table--getting a one to many join of attributes to spatial tableSpatialAfter joining attribute to spatial data
33 Attribute Operations: Joining and Relating Tables associating spatial layer to non-spatial table (contd.)Relate: many to one relationship, attributes not appendedAssociate country layer with its multiple cities (many to one)Note: if we flip these tables we can do a join since there is only one country for each city (one to many)For both Joins and Relates:Association exists only in the map documentUnderlying files not changed unless export dataIf joined Paris to France, for example, we lose Lyon and Marseille, therefore use relate
35 Advanced Applications: Proximity Analysis Nearest Neighborlocation (distance) relative to nearest neighbor ( points or polygon centroids)location (distance) relative to nearest objects of selected other types (e.g. to line, or point in another layer, or polygon boundary)Requires only one output columnaltho generalizable to kth nearest neighborPoint Pattern Analysisis pattern?Random Clustered DispersedRequires the application of Spatial Statistics such asNearest neighbor statisticMoran’s Iwhich are based on proximity of points to each otherArcToolbox>Spatial Statistics ToolsFull matrixmeasure location of each object relative to every other objectrequires output matrix with as many columns as rows in input table
36 Advanced Applications: Network Analysis Network-based Districtingexpand from site along network until criteria (time, distance, cost, object count) is reached; then assign area to districtcreating market areas, attendance zones, etcessentially network-based bufferingNetwork-based Allocationassign locations to the nearest center based upon travel thru networkassign customers to pizza delivery outletsdraw boundaries (lines of equidistance between 2 centers) based on the aboveNetwork-based market area delimitationEssentially, network-based polygon tesselationRoutingshortest path between two pointsdirection instructions (locating hotel from airport)travelling salesman: shortest path connecting n pointsbus routing, delivery driversIn all cases, ‘distance’ may bemeasured in miles, time, cost orother ‘friction’ (e.g pipe diameterfor water, sewage, etc.).Arc or node attributes (e.g one-waystreets, no left turn) may also becritical.
37 Advanced applications: Surface Analysis Cross-section Drawings and Volumeselevation (or slope) values along a lineVolume & cut-and-fill calculationCross-section easy to produce for raster, more difficult for vector especially if uses contours linesViewshed/Visibilityterrain visible from a specific pointapplicationsvisual impact of new constructionselect scenic overlooksMilitaryContouringLines joining points of equal (vertical) valueFrom raster, massed-points or breakline dataSlope Transformfit a plane to the 3 by 3 neighborhood around every cell, or use a TINoutput layer is the slope (first derivative) of the plane for each cellAspect Transformdirection slope faces: (E-W oriented ridge has slopes with northern and southern aspects)aspect normally classified into eight 45 degree categoriescalculate as horizontal component of the vector perpendicular to the surface
38 Advanced Applications: Convex Hull Formally: the smallest convex polygon (no concave angles) able to contain a set of pointsInformally: a rubber band wrapped around a set of pointsJust as a centroid is a point representation for a polygon, the convex hull is the polygon representation for a set of pointsGo to the following web site for a neat application showing how convex hull changes as you move points aroundNo!
39 Advanced Applications: Thiessen (Dirichlet, Voronoi) Polgons and Delaunay Triangles Thiessen Polygons(or proximal regionsor proximity polygons)polygons generated from a point layer such that any location within a polygon is closer to the enclosed point than to a point within any other polygonthey divide the space between the points as ‘evenly’ as possibleused for market area delimitation, rain gauge area assignment, contouring via Delaunay triangles (DTs), etc.elevation, slope and aspect of triangle calculated from heights of its three cornersDTs are as near equiangular as possible and longest side is as short as possible, thus minimizes distances for interpolationADelaunay TrianglesAThiessen neighbors of point A share a common boundary. Delauney triangles are formed by joining point to its Thiessen neighbors.
40 Specialized Applications Remote Sensing/Digital Image Processingreflectance value (usually 8 bit; 256 values) collected for each bands (wavelength area) in the electro-magnetic spectrum1 band for grey scale (Black & white)3 for colorup to 200 or so for ‘hyperspectral’permits creation of image‘spectral signature’: set of reflectance values/ranges over available bands typifying a specific phenomenaprovides basis for identification of phenomenaLocation Science/Network ModelingNetwork based models for optimum location decisions for (e.g.)police beatsSchool attendance zonesBus routesHazardous material routingFire station locationRaster Modeling: 2-Duse of direction and friction surfaces to develop models for:spread of pollutiondispersion of forest firesSurface Modeling: 3-Dflood potentialground water/reservoir studiesViewshed/visibility analysisSpatial Statistics/Econometricsanalyses on spatial data which explicitly incorporates relative location or proximity property of observationsGlobal (applies to entire study area)spatial autocorrelationRegressions adjusted for spatial autocorrelationLocal (separately calculated for local areas)LISA (local indicators of spatial autocorrelation)Geographically weighted regressionWe offer one or more courses on each!
41 Implementation of Advanced and Specialized Applications in ArcGIS 8/9 Extensions support many of the Advanced and some Specialized ApplicationsSpatial Analyst extension provides 2-D modeling of GRID (raster) data (AV 3.2 and 8/9)3-D Analyst extension provides 3-D modeling (AV 3.2 and 8/9)Geostatistical Analyst extension provides interpolation (ArcGis 8/9 only)Network Analyst extension (3.2 only) and ArcLogistics Route (standalone) for routing and network analysisImage Analyst extension for remote sensing applications in AV 3.2Leica Image Analysis and Stereo Analyst for ArcGIS 8 (9 version not yet released-Fall ’04)Spatial Statistics Tools in ArcToolbox provide spatial statistics (centroid, etc..)ArcScripts support other Advanced Applications and Specialized ApplicationsArcScripts (in Visual Basic, C++, etc.) are used to customize ArcGIS 8A variety of scripts available at >downloadsNote: ArcScripts written in Avenue work only in ArcView 3 and will not work in ArcGIS 8/9Many functions previously requiring Avenue scripts for AV 3.2 are built into ArcGIS 8/9Specialized Software PackagesRemote Sensing packages such as Leica GeoSystems Imagine (formerly ERDAS Imagine)For links to some of these packages go to:
43 Implementing Spatial Measurement in ArcView 3.2 Unlike in ArcGIS 8.1 where spatial measurements are provided automatically, in AV 3.2 spatial measurement often has to be implemented using Avenue code:in functional expressionsin scriptsUsing functional expression for areas and lengths:Use Edit/Add field to add a new variable to atttributes of…table called area (or similar)Use Field/calculate and make this variable equal to: [Shape].ReturnAreaCalculation is based on map units irrespective of defined distance units.If map units are feet, to obtain square miles use: [Shape].ReturnArea/5280/5280If file is a polyline file (arcs), for length of arcs use: [Shape].ReturnLengthUsing a Script for areas, perimeters and lengthsIn Project window, select Script and click new button to open script windowUse Script/load text file to load code from an existing text filee.g. arcview\samples\scripts\calcapl.ave will calculate areas, perimeters, lengthsClick the “check mark” icon to compile the code.Open a View and be sure the theme you want processed is active.Click on script window then click the Runner icon to run script.variables measuring area and perimeter will be added to theme table
44 Implementing Spatial Matching in ArcView 3.2 Available in two places (plus additional user extensions such as districting)via Theme/select by themethis selects features of the active theme which relate in some specified spatial manner to another themeif desired, selected features may be saved later to a new theme via Theme/convert to shape filevia Geoprocessing Wizard Extension (use File/Extensions to load)this creates a new theme (shape file) & combines attribute tables from 2 or more input themesSix options available for different types of matchingOptions in Geoprocessing Wizard (use View/Geoprocessing Wizard to activate)Dissolve features based on an attributeUse for spatial aggregation/dissolvingMerge themes togetherUse for edge matchingClip one theme based on anotherUse one theme to limit features in another theme (e.g. limit a Texas road theme to Dallas county only)Intersect two themesUse for polygon on polygon overlayUnion two themesAssign data by location (Spatial Join)Use for: points in polygonlines in polygonpoints on lines (to calculate distance to nearest line)points on points (to calculate distance to “nearest neighbor” point)Scripts and extensions can provide additional capabilitiesDownload from ArcScripts at ESRIscripts.cfmPlace extensions (.avx) in your folder Arcview/ext32The extension district.avx is good for doing spatial aggregation or “districting”
45 Using Extensions and Scripts in ArcView 3.2 Obtain copy of script or extensionWrite yourself with Avenue languageSupplied with ArcView in folder: arcview/samples/scripts or arcview/samples/extGo to ArcView Help/Contents/Sample Scripts and Extensions for documentationBuy from ESRI and other companiesSupplied free by ESRI or users and available on ESRI web site at: Select Avenue languageor go to and click SupportBe sure to print or download documentation/descriptionTo load and use an extensionPlace .avx file in arcview/ext32 folderOpen ArcView, choose File/extensions, place tick next to name, click OKTo load and use a scriptIn Project window, select Script and click new button to open script windowUse Script/load text file to load code from existing text file containing avenue code (.ave)e.g. \av_gis30\arcview\samples\scripts\calcapl.ave will calculate areas, perimeters, lengthsClick the “check mark” icon to compile the code.Take steps within ArcView as appropriate for specific scripte.g. Open a View and be sure the theme you want processed is active.Click on script window then click the “Runner" icon to run script.e.g. variables measuring area and perimeter will be added to theme table
46 Some Example Avenue Scripts for ArcView 3 Avenue scripts and extensions for AV 3.2 can be downloaded from ESRI Web site to do many basic, advanced and specialized applications not available in standard products. Some examples are:Addxycoo.ave: adds X,Y coordinates of points (e.g of geocoded addresses), or of centroid for polygons, to attributes of … filePolycen.ave: creates point theme containing polygon centroidsDwizard.zip: various districting applicationsUse avdist31b which is an updateLine.zip: enhanced buffering of linesNearestneighbor.zip: nearest neighbor analysisFor more scripts, go to: Select Avenue language