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Analysis and Modeling in GIS 1 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 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 layers Prediction: 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 2 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals The Analysis Challenge • Recognizing which generic GIS analytic capability (or combination) can be used to solve your problem: – meet an operational need – answer a question posed by your boss or your board – address a scientific issue and/or test a hypothesis Send mailings to property owners potentially affected by a proposed change in zoning Determine 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 corridor Determine the proportion of a region covered by igneous extrusions Do 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? 3 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Availability of Capabilities in GIS Software • Descriptive Focus: Basic Desktop GIS packages – Data editing, description and basic analysis – ArcView – Mapinfo – Geomedia • Analytic Focus: Advanced Professional GIS systems Capabilities move – More sophisticated data editing plus more advanced „down the chain‟ analysis over time. – ARC/INFO, MapInfo Pro, etc. Provided through extra cost Extensions In earlier generation or professional versions of desktop packages GIS systems, use of • Prediction: Specialized modeling and simulation advanced applications – via scripting/programming within GIS often required learning » VB and ArcObjects in ArcGIS another package with » Avenue scripts in ArcView 3.2 a different user » AMLs in Workstation ARC/INFO (v. 7) interface and Write your own or download from ESRI Web site operating system – via specialized packages and/or GISs (usually UNIX). » 3-D Scientific Visualization packages » transportation planning packages e.g TransCAD » ERDAS, ER Mapper or similar package for raster Description and Basic Analysis (Table of Contents) • Spatial Operations • Attribute Operations Vector – spatial measurement – record selection – Centrographic statistics » tabular via SQL – buffer analysis » „information clicking‟ – spatial aggregation with cursor » redistricting – variable recoding » regionalization » classification – record aggregation – Spatial overlays and – general statistical joins analysis Raster – table relates and joins – neighborhood analysis/spatial filtering – Raster modeling 5 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial operations: Spatial Measurement Spatial measurements: Comments: • distance measures • Cartesian distance via Pythagorus – between points – from point or raster dij ( Xi Xj ) 2 (Yi Yj ) 2 to polygon or zone boundary – between polygon centroids Used for projected data by ArcMap measure tools • polygon area • Spherical distance via spherical coordinates Cos d = (sin a sin b) + (cos a cos b cos P) • polygon perimeter where: d = arc distance • polygon shape a = Latitude of A b = Latitude of B • volume calculation P = degrees of long. A to B Used for unprojected data by ArcMap measure tools – e.g. for earth moving, reservoirs • possible distance metrics: • direction determination – straight line/airline – e.g. for smoke plumes – city block/manhattan metric – distance thru network ArcGIS geodatabases contain automatic – time/friction thru network variables: • shape often measured by: shape.length: line length or perimeter = 1.0 for circle polygon perimeter area x 3.54 = 1.13 for square Large for complex shape shape.area: polygon area • Projection affects values!!! Automatically updated after editing. Distances depend on For shapefiles, these must be calculated projection. e.g. by opening attribute table and applying Perimeter to area ratio Calculate Geometry to a column (AV 9.2) differs 6 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial operations: Spatial Measurement SHAPE AREA PERIMETER CNTY_ CNTY_ID NAME FIPS Shape Index Polygon 0.265 2.729 2605 2605 Anderson 48001 1.50 Polygon 0.368 2.564 2545 2545 Andrews 48003 1.19 Polygon 0.209 2.171 2680 2680 Angelina 48005 1.34 Polygon 0.072 2.642 2899 2899 Aransas 48007 2.78 Polygon 0.233 1.941 2335 2335 Archer 48009 1.14 Polygon 0.233 1.941 2103 2103 Armstrong 48011 1.14 Polygon 0.299 2.278 2870 2870 Atascosa 48013 1.18 Polygon Polygon 0.224 1.900 2471 2471 Dallas 48113 1.13 Polygon 0.222 1.889 2481 2481 Dawson 48115 1.13 Polygon 0.368 2.580 2106 2106 Deaf Smith 48117 1.20 Polygon 0.072 1.421 2386 2386 Delta 48119 1.50 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) 7 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial Measurement: Calculating the Area of a Polygon 10 Area=(2 x 4)/2=4 Area=(3 x 4)=12 A = B - C 10 4,7 7,7 - 5 5 5 = 5 0 7,3 2,3 0 5 10 0 5 10 0 5 10 Area=(5 x 1)/2=2.5 6,2 The actual algorithm used obtains the area of A by 0 0 5 10 calculating the areas of B and C, and then subtracting. The actual formulae used is as follows: The area of the above i 1 polygon is 18.5, based on n (X2 - X1) ( Y1 Y2)/2 dividing it into rectangles Its implementation in Excel is shown below. and triangles. However, i X Y X2-X1 (Y1+Y2)/2 product sum 1 2 3 2 5 10 10 this is not practical for a 2 3 4 7 7 7 3 0 7 5 21 0 31 31 complex polygon. 4 5 7 6 3 2 -1 -4 2.5 2.5 -2.5 -10 28.5 18.5 Area of triangle = 2 3 (base x height)/2 8 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial Operations: Centrographic Statistics • Basic descriptors for spatial point distributions • Two dimensional (spatial) equivalents of standard descriptive statistics (mean, standard deviation) for a single-variable distribution Measures of Centrality (equivalent to mean) – Mean Center and Centroid Measures of Dispersion (equivalent to standard deviation or variance) – Standard Distance – Standard Deviational Ellipse • Can be applied to polygons by first obtaining the centroid of each polygon • Best used in a comparative context to compare one distribution (say in 1990, or for males) with another (say in 2000, or for females) 9 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Centroid and Mean Center • balancing point for a spatial distribution n n – analogous to the mean Xi Yi – single point representation for a polygon (centroid) X i 1 , Y i 1 – single point summary for a point distribution (mean center) n n – 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 for – summarizing change over time in a distribution (e.g US pop. centroid every 10 years) – placing labels for polygons • for weird-shaped polygons, centroid may not lie within polygon centroid outside polygon Note: many ArcView applications calculate only a “psuedo” centroid: the coordinates of the Can be implemented via: bounding box (the extent) of the polygon ArcToolbox>Spatial Statistics Tools>Measuring Geographic Distributions>Mean Center 10 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 10 Calculating the centroid of a polygon or the mean center of 4,7 7,7 a set of points. (same example data as 1 2 3 for area of polygon) 5 2 4 7 3 7 7 4 7 3 n n 2,3 7,3 5 6 2 Xi Y i X i 1 ,Y i 1 sum 26 22 n n 6,2 Centroid/MC 5.2 4.4 0 0 5 10 10 Calculating the weighted mean center. Note how it is pulled 4,7 7,7 toward the high weight point. i X Y weight wX wY 5 1 2 3 3,000 6,000 9,000 n n 7,3 2 3 4 7 7 7 500 400 2,000 2,800 3,500 2,800 wiXi wY i i X i 1 ,Y i 1 w w 2,3 4 7 3 100 700 300 5 6 2 300 1,800 600 i i 6,2 sum 26 22 4,300 13,300 16,200 0 w MC 3.09 3.77 0 5 10 11 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 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 coast For 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, pp. Source: US Statistical Abstract 2003 65-69 Standard Distance Deviation single unit measure of the spread or dispersion of a distribution. • Is the spatial equivalent of standard deviation for a single variable • Equivalent to the standard deviation of the distance of each point from the mean center • Given by: i1 ( Xi Xc ) 2 i 1 (Yi Yc ) 2 n n N which by Pythagoras i1 reduces to: n diC 2 N ---the square root of the average squared distance ---essentially the average distance of points from the center We can also weight each point and calculate weighted standard distance (analogous to weighted mean center.) 13 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Standard Distance Deviation Example 10 Circle with radii=SDD=2.9 4,7 7,7 5 7,3 2,3 i X Y (X - Xc)2 (Y - Yc)2 6,2 1 2 3 10.2 2.0 0 2 4 7 1.4 6.8 3 7 7 3.2 6.8 0 5 10 4 7 3 3.2 2.0 i X Y (X - Xc)2 (Y - Yc)2 5 6 2 0.6 5.8 1 2 3 10.2 2.0 sum 26 22 18.8 23.2 2 4 7 1.4 6.8 Centroid 5.2 4.4 3 7 7 3.2 6.8 sum 42.00 4 7 3 3.2 2.0 divide N 8.40 5 6 2 0.6 5.8 sq rt 2.90 sum 26 22 18.8 23.2 Centroid 5.2 4.4 sum of sums 42 divide N 8.4 sq rt 2.90 ( Xi Xc ) 2 i 1 (Yi Yc ) 2 n n sdd i 1 N 14 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 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 bias – doesn‟t capture the shape of the distribution. • The standard deviation ellipse gives dispersion in two dimensions • Defined by 3 parameters – Angle of rotation – Dispersion along major axis – Dispersion along minor axis The major axis defines the direction of maximum spread of the distribution The minor axis is perpendicular to it and defines the minimum spread 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, see Lee and Wong Statistical Analysis with ArcView GIS pp. 48-49 (1st ed.), pp 203-205 (2nd ed.) 16 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial Operations: buffer zones • region within „x‟ distance units • buffer any object: point, line or polygon • use multiple buffers at progressively polygon buffer greater distances to show gradation • may define a „friction‟ or „cost‟ layer Examples so that spread is not linear with • 200 foot buffer around property distance where zoning change requested • Implement in Arcview 3.2 with • 100 ft buffer from stream center Theme/Create buffers line limiting development in ArcGIS 8 with • 3 mile zone beyond city ArcToolbox>Analysis Tools>Buffer boundary showing ETJ (extra territorial jurisdiction) point • use to define (or exclude) areas buffers line as options (e.g for retail site) or buffer for further analysis • in conjunction with „friction layer‟, simulate spread of fire Note: only one layer is involved, but the buffer can be output as a new layer Spatial Operations: Grouping/combining polygons—is spatial aggregation applied to one polygon layer only. • districting/redistricting Criteria may be: – grouping contiguous polygons – formal (based on in situ characteristics) into districts e.g. city neighborhoods – functional (based on flows or links): – original polygons preserved e.g. commuting zones • Regionalization (or dissolving) Groupings may be: – contiguous – grouping polygons into – non-contiguous contiguous regions Boundaries for original polygons: – original polygon boundaries – may be preserved dissolved – may be removed (called dissolving) • classification Examples: – grouping polygons into non- • elementary school zones to high school contiguous regions attendance zones (functional districting) – original boundaries usually • election precincts (or city blocks) into dissolved legislative districts (formal districting) – usually „formal‟ groupings • creating police precincts (funct. reg.) • creating city neighborhood map (form. reg.) Implement in ArcView 9 thru • grouping census tracts into market ArcToolbox>Generalization>Dissolve segments--yuppies, nerds, etc (class.) • creating soils or zoning map (class) Districting: elementary school attendance zones grouped to form junior high zones. Regionalization: census tracts grouped into neighborhoods Classification: cities categorized as central city or suburbs soils classified as igneous, sedimentary, metamorphic 19 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial Operations: Spatial Matching: Spatial Joins and Overlays Examples • combine two (or more) layers to: – select features in one layer, &/or • assign environmental samples – create a new layer (points) to census tracts to estimate • used to integrate data having different exposure per capita (point in spatial properties (point v. polygon), or polygon) different boundaries (e.g. zip codes • identify tracts traversed by freeway and census tracts) for study of neighborhood blight • can overlay polygons on: (polygon on lines) – points (point in polygon) • integrate census data by block with – lines (line on polygon) sales data by zip code (polygon on – other polygons (polygon on polygon) polygon) – many different Boolean logic combinations possible • Clip US roads coverage to just » Union (A or B) cover Texas (polygon on line) » Intersection (A and B) • Join capital city layer to all city » A and not B ; not (A and B) layer to calculate distance to • can overlay points on: nearest state capital – Points, which finds & calculates distance to nearest point in other theme (point on point) – Lines, which calculates distance to nearest line 20 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Example: Spatial Matching: Clipping and Erasing (sometimes referred to as spatial extraction) •CLIP - extracts those features from an input •ERASE - erases the input coverage that overlap with a clip coverage. coverage features that overlap This is the most frequently used polygon with the erase coverage overlay command to extract a portion of a coverage to create a new coverage. polygons. 21 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Example: Spatial Matching via Polygon-on-Polygon Overlay: Union Land Use a. b. c. The two layers (land use & drainage basins) do not Drainage Atlantic A. have common Basins G. boundaries. GIS creates Gulf combined layer with all possible combinations, Combined layer aA bA cA permitting calculation of bG land use by drainage aG cG basin. Note: 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. Another example In set theory terms, the outcome 1 2 of the above would simply be: 3 GIS Union Set Theory Union Implementing Spatial Matching in ArcGIS 9 Available in three places • via Selection/Select by Location – this selects features of one layer(s) which relate in some specified spatial manner to the features in another layer – if desired, selected features may be saved later to a new theme via Data/Export Data – Individual features are not themselves modified • via 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 polygon lines in polygon points 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 themselves • via ArcToolbox – Generally these tools modify geographic feature, thus they create a new layer (e.g. shape file) – Tools are organized into multiple categories ArcToolbox Examples • Dissolve features based on an attribute – Combine contiguous polygons and remove common border – ArcToolbox>Generalization>Dissolve • Clip one layer based on another – ArcToolbox>Analysis Tools>Extract>Clip – Use 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>Intersect – Use for polygon on polygon overlay • Union two layers (covers full extent of both layers) – ArcToolbox>Analysis Tools>Overlay>Intersect – Use for polygon on polygon overlay Spatial Operations: neighborhood analysis/spatial filtering • spatial convolution or filter • low frequency ( low pass) filter: – applied to one raster layer mean filter – value of each cell replaced by some function of the values of – cell replaced by the mean for itself and the cells (or neighborhood polygons) surrounding it – equivalent to weighting – can use „neighborhood‟ or (mutiplying) each cell by „window‟ of any size 1/9 = .11 (in 3x3 case) » 3x3 cells (8-connected) – smooths the data » 5x5, 7x7, etc. – differentially weight the cells – use larger window for greater to produce different effects smoothing – kernel for 3x3 mean filter: median filter 1/9 1/9 1/9 – use median (middle value) weights must 1/9 1/9 1/9 sum to 1.0 instead of mean 1/9 1/9 1/9 – smoothing, especially if data has extreme value outliers 24 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial Operations: spatial filtering -- high pass filter high frequency (high pass) filter standard deviation filter negative weight filter (texture transform) – exagerates rather than smooths – calculate standard deviation of local detail neighborhood raster values – used for edge detection – high SD=high texture/variability – low SD=low texture/variability cell values (vi ) on – again used for edge detection each side of edge filtered values for – neighorhoods spanning border 2 5 highlighted pixel have large SD „cos of 1(5)(9)+5(5)(-1)+3(2)(-1) = 14 variability 1(2)(9)+5(2)(-1)+3(5)(-1) = -7 –kernel for example (wi) 1(2)(9)+8(2)(-1) = 2 -1 -1 -1 1(5)(9)+8(5)(-1) = 5 -1 9 -1 f .v . w -1 -1 -1 i i i 25 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Spatial Operations: raster–based modelling • Relating multiple rasters • Suitability modeling • Processes may be: 0 0 1 0 1 0 2 Site 0 soil slope for – Local: one cell only options sale – Neighborhood: cells relating 1 0 1 1 1 1 3 2 to each other in a defined • Diffusion Modeling manner – Zonal: cells in a given section System at Incidence Probability – Global: all cells matrix mask time t+1 • ArcGIS implementation: – All raster analyses require • Connectivity Modeling either the Spatial Analyst or 3-D Analyst extensions Initial Connectivity Resultant – Base ArcView can do no State matrix State more than display an image (raster) data set 26 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Attribute Operations: record selection or extraction --features selected on the map are identified in the table (and visa versa) Select by Attribute (tabular) Outputs may be: • Independent selection by clicking table rows: – Open Attribute Table & click on grey selection box at • Simultaneously highlighted start of row (hold ctrl for multiple rows) records in table, and features • Create SQL query on map – use Selection/Select by Attribute • New tables and/or map layers • use table Relates /Joins to select specific data Select by Graphic Examples • Manually, one point at a time • Use SQL query to select all – use Select Features tool zip codes with median • within a rectangle or an irregular polygon incomes above $50,000 – use Selection/Select by Graphic (tabular) • within a radius (circle) around a point or points • identify zip codes within 5 – use Selection/Select by Location (are wthin distance) mile radius of several Select by Location potential store sites and sum • By using another layer household income (graphic) – Use Selection/Select by Location • show houses for sale on map, (same as Spatial Matching discussed previously) and click to obtain picture and Hot Link additional data on a selected • Click on map to „hot link‟ to pictures, graphs, or house (hot link) other maps 27 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Attribute Operations: statistical analysis on one or more columns in table • univariate (one variable or column) – central tendency: mean, median, mode – dispersion: standard deviation, min, max – To obtain these statistics in ArcGIS: » Right click in T of C and select Open attribute table » Right click on column heading and select Statistics • bivariate (relating two variables or columns) – interval and nominal scale variables: sum or mean by category » average crop yield by silt-sand-clay soil types » To implement in ArcGIS, proceed as above but use Summarize – two interval scale variables: correlation coefficients » income by education » ArcScripts 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 28 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Attribute Operations: variable recoding • establishing/modifying number of classes and/or their boundaries for continuous variable. Options for ArcGIS – natural 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-- Implement in ArcGIS via: or equal area under the frequency distribution) Right click in T of C, select – equal interval (user selects # of classes) Properties, then Symbology tab (equal width classes on variable) – Defined interval (user selects width of classes) (assumes a Normal distribution) (equal width classes on variable) – standard deviation 25% 25% Equal area % 23% 23% (categories based on 1,2, etc, SDs 14% 34% 34% 14% Equal interval % above/below mean) Standard Deviation – Manual (user defined) -2 -1 0 1 2 Equal interval score -.68 0 .68 » whole numbers (e.g. 2,000) Equal area score » meaningful to phenomena (e.g zero, 32o) • aggregating categories on a nominal (or ordinal) variable – pine and fir into evergreen No change in number of records (observations). 29 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Attribute Operations: record aggregation • combining two or more records Fips PMSA_90 PMSA_93 Pop90 Pop95_est Pop90-95% MedInc89 Suburb Name 48085 1920 1920 264036 346232 5.93 46020 1 Collin into one, based on common 48113 1920 1920 1852810 1959281 1.09 31605 0 Dallas values on a key variable 48121 1920 1920 273525 334070 4.22 36914 1 Denton • the attribute equivalent of 48139 1920 48213 1920 1920 85167 58543 94223 64293 2.03 1.87 30553 20747 1 1 Ellis Henderson regionalization or classification 48231 1920 64343 66972 0.78 25317 1 Hunt • equivalent of PROC 48257 1920 1920 52220 60114 2.88 27280 1 Kaufman 48397 1920 1920 25604 32725 5.30 42417 1 Rockwall SUMMARY in SAS 48221 2800 28981 33384 2.89 31627 1 Hood • interval scale variables can be 48251 2800 2800 97165 106181 1.77 30612 1 Johnson 48367 2800 2800 64785 73794 2.65 30592 1 Parker aggregated using mean, sum, 48439 2800 2800 1170103 1278606 1.77 32335 0 Tarrant max, min, standard deviation, Source: US Bureau of the Census etc. as appropriate MedInc=Median Household Income. Pop90 as of April 1. Pop95 as of July 1. • ordinal and nominal require special consideration Fips PMSA_90 PMSA_93 Pop90 Pop95_est Pop90-95% MedInc89 Suburb Name • example: aggregate county data 1920 2676248 2957910 2.00 32607 7 Dallas to states, or county to CMSA 2800 1361034 1491965 1.83 31292 3 Fort Worth Record count decreases (e.g. from 12 sum sum re-calc. count to 2) average Type of processing: of medians! 30 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Attribute Operations: Joining and Relating Tables associating spatial layer to non-spatial table Join: one to one, or one to many, relationship appends attributes Associate table of country capitals with country layer: only one capital for each country (one to one) Country Code Country Country Code Capital Country Code Country Capital 29 France 199 Caracas 9 UK London 68 Saudi Arabia 96 Manila 29 France Paris 106 Chad 68 Riyadh 68 Saudi Arabia Riyadh 248 Spain 29 Paris 96 Philippines Manila 199 Venezuela 106 N'Djamena 106 Chad N'Djamena 9 UK 9 London 199 Venezuela Caracas 96 Philippines 248 Madrid 248 Spain Madrid Layer Attribute Table NonSpatial Table Layer Attribute Table after Join 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) Gov. Code Country Gov. Code Type Gov. Code Country Type 20 France 10 Absolute Monarchy 20 France Republic 30 Vietnam 15 Const. Monarchy 30 Vietnam Communist State 15 UK 20 Republic 15 UK Const. Monarchy 20 Argentina 30 Communist State 20 Argentina Republic 10 Saidi Arabia 45 Parliamentary Democracy 10 Saudi Arabia Absolute Monarchy 15 Sweden 15 Sweden Const. Monarchy 45 Portugal 45 Portugal Parliamentary Democracy Layer Attribute Table NonSpatial Table Layer Attribute Table after Join 31 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 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 table NAME FIPS CODE POP2000 Alabama 01 AL 4,447,100 Alaska 02 AK 626,932 ….. Georgia 13 GA 8,186,453 Hawaii 15 HI 1,211,537 Idaho 16 ID 1,293,953 ….. Wisconsin 55 WI 5,363,675 Wyoming 56 WY 493,782 Spatial 51 states Total 282,421,906 FID SHAPE NAME FIPS CODE POP2000 0 Polygon Alabama 01 AL 4,447,100 1 Polygon Alaska 02 AK 626,932 ….. 11 Polygon Georgia 13 GA 8,186,453 12 13 Polygon Polygon Hawaii-Hawaii 15 Hawaii-Maui 15 HI HI 1,211,537 1,211,537 After joining 14 Polygon Hawaii-Oahu 15 HI 1,211,537 15 Polygon Hawaii-Kauai 15 HI 1,211,537 attribute to 16 Polygon Idaho 16 ID 1,293,953 ….. spatial data 53 Polygon Wisconsin 55 WI 5,363,675 54 Polygon Wyoming 56 WY 493,782 Total 286,056,517 32 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Attribute Operations: Joining and Relating Tables associating spatial layer to non-spatial table (contd.) Relate: many to one relationship, attributes not appended Associate country layer with its multiple cities (many to one) Country Code Country Country Code City 29 France 129 Mombasa 129 Nairobi 68 Saudi Arabia 106 Chad 29 Paris If joined Paris to France, for 29 Lyon 248 Spain 199 Venezuela 29 Marseille example, we lose Lyon and 60 Katmandu 9 UK 248 Madrid Marseille, therefore use relate 96 Philippines Layer Attribute Table 248 Barcelona 248 Valencia NonSpatial Table 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 document • Underlying files not changed unless export data 33 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Analysis Options: Advanced & Specialized (Table of Contents) Advanced Specialized • Proximity/point pattern analysis • Remote Sensing image processing and classification – nearest neighbor layer – distance matrix layer • raster modeling • surface analysis • 3-D surface modeling – cross section creation • spatial statistics/statistical – visibility/viewshed modeling • network analysis • functionally specialized – routing – transportation modeling » shortest path (2 points) – land use modeling » travelling salesman (n points) – hydrological modeling – time districting – etc. – allocation • Convex Hull • Thiessen Polygon creation 34 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Advanced Applications: Proximity Analysis Nearest Neighbor • location (distance) relative to nearest Point Pattern Analysis neighbor ( points or polygon centroids) • location (distance) relative to nearest objects is pattern? of selected other types (e.g. to line, or Random Clustered Dispersed point in another layer, or polygon boundary) Requires only one output column – altho generalizable to kth nearest neighbor Requires the application of Full matrix Spatial Statistics such as • measure location of each object relative •Nearest neighbor statistic to every other object •Moran‟s I – requires output matrix with as many columns as rows in input table which are based on proximity of points to each other ArcToolbox>Spatial Statistics Tools 35 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Advanced Applications: Network Analysis Network-based Districting Routing • expand from site along network until • shortest path between two criteria (time, distance, cost, object points count) is reached; then assign area to district – direction instructions (locating – creating market areas, attendance hotel from airport) zones, etc • travelling salesman: shortest – essentially network-based buffering path connecting n points Network-based Allocation – bus routing, delivery drivers • assign locations to the nearest center based upon travel thru network In all cases, „distance‟ may be – assign customers to pizza delivery measured in miles, time, cost or outlets other „friction‟ (e.g pipe diameter • draw boundaries (lines of for water, sewage, etc.). equidistance between 2 centers) Arc or node attributes (e.g one-way based on the above streets, no left turn) may also be – Network-based market area critical. delimitation – Essentially, network-based polygon tesselation 36 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Advanced applications: Volumes Surface Analysis Cross-section Drawings and along a • elevation (or slope) values line Slope Transform • Volume & cut-and-fill calculation • fit a plane to the 3 by 3 neighborhood around every cell, or • Cross-section easy to produce for use a TIN raster, more difficult for vector • output layer is the slope (first especially if uses contours lines derivative) of the plane for each Viewshed/Visibility cell • terrain visible from a specific point Aspect Transform • applications • direction slope faces: (E-W – visual impact of new construction oriented ridge has slopes with northern and southern aspects) – select scenic overlooks • aspect normally classified into – Military eight 45 degree categories • Contouring • calculate as horizontal component – Lines joining points of equal of the vector perpendicular to the (vertical) value surface – From raster, massed-points or breakline data 37 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Advanced Applications: Convex Hull • Formally: the smallest convex polygon (no concave angles) able to contain a set of points • Informally: a rubber band wrapped around a set of points No! • Just as a centroid is a point representation for a polygon, the convex hull is the polygon representation for a set of points • Go to the following web site for a neat application showing how convex hull changes as you move points around –http://www.cs.princeton.edu/~ah/alg_anim/version1/ConvexHull.html 38 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Advanced Applications: Thiessen (Dirichlet, Voronoi) Polgons Thiessen Polygons (or proximal regions and Delaunay Triangles or 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 polygon A • they divide the space between the points as „evenly‟ as possible • used for market area delimitation, rain gauge area assignment, contouring via Delaunay triangles (DTs), etc. Delaunay Triangles • elevation, slope and aspect of triangle calculated from heights of its three corners • DTs are as near equiangular as possible and longest side is as short as possible, thus A minimizes distances for interpolation Thiessen neighbors of point A share a common boundary. Delauney triangles are formed by joining point to its Thiessen neighbors. 39 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Specialized Applications Remote Sensing/Digital Image Raster Modeling: 2-D Processing • use of direction and friction surfaces to • reflectance value (usually 8 bit; 256 develop models for: values) collected for each bands – spread of pollution (wavelength area) in the electro- – dispersion of forest fires magnetic spectrum Surface Modeling: 3-D – 1 band for grey scale (Black & white) – flood potential – 3 for color – ground water/reservoir studies – up to 200 or so for „hyperspectral‟ – Viewshed/visibility analysis – permits creation of image Spatial Statistics/Econometrics • „spectral signature‟: set of reflectance values/ranges over available bands • analyses on spatial data which explicitly typifying a specific phenomena incorporates relative location or proximity property of observations – provides basis for identification of phenomena Global (applies to entire study area) Location Science/Network Modeling – spatial autocorrelation – Regressions adjusted for spatial • Network based models for optimum autocorrelation location decisions for (e.g.) Local (separately calculated for local areas) – police beats – LISA (local indicators of spatial – School attendance zones autocorrelation) – Bus routes – Geographically weighted regression – Hazardous material routing – Fire station location We offer one or more courses on each! 40 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Implementation of Advanced and Specialized Applications in ArcGIS 8/9 Extensions support many of the Advanced and some Specialized Applications • Spatial 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 analysis • Image Analyst extension for remote sensing applications in AV 3.2 – Leica 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 Applications • ArcScripts (in Visual Basic, C++, etc.) are used to customize ArcGIS 8 – A variety of scripts available at http://support.esri.com/ >downloads – Note: ArcScripts written in Avenue work only in ArcView 3 and will not work in ArcGIS 8/9 – Many functions previously requiring Avenue scripts for AV 3.2 are built into ArcGIS 8/9 Specialized Software Packages • Remote Sensing packages such as Leica GeoSystems Imagine (formerly ERDAS Imagine) • For links to some of these packages go to: http://www.utdallas.edu/~briggs/other_gis.html 41 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Appendix Implementing Spatial Analysis in ArcView 3.2/3.3 42 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 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 expressions – in scripts • Using 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].ReturnArea – Calculation is based on map units irrespective of defined distance units. – If map units are feet, to obtain square miles use: [Shape].ReturnArea/5280/5280 – If file is a polyline file (arcs), for length of arcs use: [Shape].ReturnLength • Using a Script for areas, perimeters and lengths In Project window, select Script and click new button to open script window Use Script/load text file to load code from an existing text file e.g. arcview\samples\scripts\calcapl.ave will calculate areas, perimeters, lengths Click 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 43 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Implementing Spatial Matching in ArcView 3.2 Available in two places (plus additional user extensions such as districting) • via Theme/select by theme – this selects features of the active theme which relate in some specified spatial manner to another theme – if desired, selected features may be saved later to a new theme via Theme/convert to shape file • via Geoprocessing Wizard Extension (use File/Extensions to load) – this creates a new theme (shape file) & combines attribute tables from 2 or more input themes – Six options available for different types of matching Options in Geoprocessing Wizard (use View/Geoprocessing Wizard to activate) • Dissolve features based on an attribute – Use for spatial aggregation/dissolving •Scripts and extensions can provide • Merge themes together additional capabilities – Use for edge matching •Download from ArcScripts at ESRI • Clip one theme based on another http://gis.esri.com/arcscripts/ – Use one theme to limit features in another theme scripts.cfm (e.g. limit a Texas road theme to Dallas county only) •Place extensions (.avx) in your • Intersect two themes folder Arcview/ext32 – Use for polygon on polygon overlay •The extension district.avx is good • Union two themes for doing spatial aggregation or – Use for polygon on polygon overlay “districting” • Assign data by location (Spatial Join) – Use for: points in polygon lines in polygon points on lines (to calculate distance to nearest line) points on points (to calculate distance to “nearest neighbor” point) 44 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals Using Extensions and Scripts in ArcView 3.2 • Obtain copy of script or extension – Write yourself with Avenue language – Supplied with ArcView in folder: arcview/samples/scripts or arcview/samples/ext » Go to ArcView Help/Contents/Sample Scripts and Extensions for documentation – Buy from ESRI and other companies – Supplied free by ESRI or users and available on ESRI web site at: http://arcsripts.esri.com/ Select Avenue language » or go to www.esri.com and click Support » Be sure to print or download documentation/description • To load and use an extension – Place .avx file in arcview/ext32 folder – Open ArcView, choose File/extensions, place tick next to name, click OK • To load and use a script In Project window, select Script and click new button to open script window Use 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, lengths Click the “check mark” icon to compile the code. Take steps within ArcView as appropriate for specific script e.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 45 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals 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 … file – Polycen.ave: creates point theme containing polygon centroids – Dwizard.zip: various districting applications » Use avdist31b which is an update – Line.zip: enhanced buffering of lines – Nearestneighbor.zip: nearest neighbor analysis For more scripts, go to: http://arcsripts.esri.com/ Select Avenue language 46 9/2/2009 Ron Briggs, UTDallas GISC 6381 GIS Fundamentals