空間統(tǒng)計書單12sademo

1、Using GeoDASoftware for Geographic Data Analysisand ExplorationDeveloped by Luc AnselinArizona State UniversitySchool of Geography and PBriggs Henan University 20101Briggs Henan University 20102Software for Spatial Analysis and StatisticsArcGIS 9 The most common GIS Softw

2、are, but $!Spatial Statistics Tools for point and polygon analysisSpatial Analyst tools for density kernelGeoStatistical Analyst Tools for interpolation of continuous surface data OpenGeoDA, Geographic Data Analysis by Luc Anselin now at Arizona StateDownload from: Runs on Vista and Windows 7 (also

3、MAC and UNIX)Earlier version called GeoDA runs only on XP (0.9.5i_6)Easy to use and has good graphic capabilities CrimeStat III download from Standalone package, free for government and education useCalculates values for spatial statistics but no GIS graphicsGood documentation and explanation of mea

4、sures and conceptsR Open Source statistical package, originally on UNIX but now has MS Windows versionHas the most extensive set of spatial statistical analysesDifficult to useNeed to learn it if you are going to do major work in this areaS-Plus the only commercial statistical package with good supp

5、ort for spatial statistics GeoDA OverviewGeoDA is a package for exploratory analysis of geographic data. Primarily analyzes polygon data, but can also do some things with point dataHas major capabilities not easily available elsewhere including: -creates spatial weights matrices with multiple option

6、s -linking and brushing between maps, histograms, scatter plots -calculates and maps Local Indices of Spatial Association (LISA or local Morans I).standard multiple regression full diagnostics for spatial effectsspatial autoregressive model for both spatial lag and spatial error modelsFree. ArcGIS n

7、ot required, but it does require a shapefile for data input.Briggs Henan University 20103Obtaining GeoDA SoftwareThe GeoDA program is on my Web site at: or go to You will have to create a new user accountdownload, unzip, and click the file OpenGeoDA.exe to start the softwareThis version (OpenGeoDA)

8、runs on Vista and Windows 7Earlier version (GeoDA095i) only runs on XPit does have some “bugs” so some things may not work or it may crash!Briggs Henan University 20104Help and Documentation for GeoDAFor help using OpenGeoDA, go to Click on Support tabFor printable manuals, go to and download geoDAd

9、oc.zipGeoda_quickstart : 25 page quick start guide to using geoda (read first)Geoda_spauto a quick guide to spatial autocorreletion measures (read next)Geoda93_manual is a 125 page manual which fully documents the softwareGeoda 95i_updates is a 64 page manual which covers bug fixes and enhancements

10、in the latest releaseNote, all the above are written for the earlier version GeoDa9.3, not OpenGeoDa but differences are small Briggs Henan University 20105OpenGeoDa Interface: 1 of 2Display and CreateFileopen a shape file: it should also contain the data to analyzeEditcopy maps, and open new maps t

11、o compareToolscreate spatial weights matrices (very good) create shapefiles: Thiessen polygons, centroids, etc create shapefiles from .dbf containing X,Y coordinates TableOpen a table (Promotion), joins, variable manipulation, joins, etc. To access more options, right click on any open windowBriggs

12、Henan University 20106OpenGeoDa Interface: 2 of 2AnalyzeMapcreate many types of choropleth mapsExplorecreates various non-spatial graphs of data Spacecalculating Spatial Autocorrelation measures Methodsstandard and spatial simple and multiple regressionOptionslists options for the currently active w

13、indow. To access options, right click on an open windowBriggs Henan University 20107Data for Demo Briggs Henan University 20108geoDAdata.zipchina.zip1. Use GeoDA to find the Centroids of the Provinces of ChinaBriggs Henan University 20109 (Need ArcInfo to do this in ArcGIS, which is expensive. GeoDA

14、 is free. )-Input the provinces shapefile: FileOpen Shape File China.shp-Open the data table: TablePromotion to see what is there-Create centroids for each province: Options Add Centroids to Table Place check mark in X coordinates and Y coordinates box, click OK-X and Y centroid coordinates are adde

15、d to the table-to keep them permanently you need to save as new shapefile Table Save to Shapefile as China_Centroids.shp-to close these files and start something new: FileClose All2. Create Thiessen Polygons forProvinces of ChinaBriggs Henan University 201010-use point file of province centroids cre

16、ated -Start the tool: ToolsShapePoints to Polygons Input File: China_Centroids.shp Output file: China_Thiessen.shp Bounding Box: leave blank (establishes outer edges)-click Create, then Close-Display the Thiessen polygonsFileOpen Shapefile China_Thiessen.shp If a map window is already open, use: Edi

17、tNew map layer China_Thiessen.shpResult not good because of outer boundary problem-to close these files and start something new: FileClose All3. Explore data with different mapsIlliteracy for Provinces of China11- Input the provinces shapefile, with data: FileOpen Shape File ChinaData.shp Map window

18、 opens showing China provinces -To see the data: TablePromotion (variables are defined in the file: chinaProvinceData.xls)-To map the data, right click on the map window and select Map Quantile Select variable to map: 1st variable: Illiteracy (% illiterate)(note: default variable via EditSelect vari

19、able does not work) -Multiple different choropleth maps available: Quantile, percentile, box map, std dev, equal interval, natural break choropleth map: color polygons based on variable value-Draw a second map:EditDuplicate map (to use the same data set)EditNew map layer (to use a different data set

20、) quantile (note the frequency counts in the map legend!)classes have equal numbers (quantities) of observations(equal areas under the frequency distribution) If use 4 categories called quartile (quarter) mapEach has 25% of dataequal interval (note the frequency counts!)classes are equal width on va

21、riablewill have different numbers of observationsstandard deviationcategories based on 1,2, etc, SDs above/below meanClasses have different numbers of observationsDifferent Choropleth Map Types: Always examine different map types and number of classes!0-11-2234%14%34%14%.68-.6823%23%25%0(Assumes a N

22、ormal distribution)25%Standard DeviationEqual area %sEqual interval %s Equal interval scoreEqual area scorenatural breaks finds “natural groupings” by minimizing the variance within each class using Jenks optimization. PercentileSimilar to quantile with 4 cabut Box mapWe are often interested in outl

23、iers: observations with very large or very small (extreme) values Box map examines extreme data values Possibly no observations in the extreme categoriesMapPercentile with “hinge” = 1.5 (or 3):Similar to quantile map with 4 categories exceptUses percentiles to identify extremes: top & bottom 1% & 10

24、%.Extremes are the tails of the distribution.Extremes here are based on the data value itself. Always* have observations in these categories, but they may not be extreme (*in theory, but sometimes not!)Different Choropleth Map Types:Identifying the extremes: Percentile Map4. Box Plots and Frequency

25、DistributionsClose all windowsExploreBox Plotrepeat for illiteracy, urban pop %, NatGrow05ExploreHistogramrepeat for illiteracy, urban pop %, NatGrow05The Box Plot: all observations are positioned based on their value on the variablethe green asterisk is the median observation The blue line is the m

26、eanthe colored center section shows the 25-75% percentilethe red T line in the upper part shows the location of upper “hinge”(value which is 1.5 times the interquartile range above the mean)the red in the lower part shows the location of lower “hinge” (value which is 1.5 times the interquartile rang

27、e below the mean) -sometimes both Ts are at the top & bottom of box (as in crime data), so no observations are beyond the hinge-sometimes no Ts show at allif they are within the interquartile rangeBriggs Henan University 2010155. Linking between maps and plotsEditDuplicate Map to create map layer Ri

28、ght click, and select MapPercentile repeat for illiteracy, urban pop %, NatGrow05 (ignore warnings) widen the legend box so that you can see frequency count arrange boxes as illustrated note that weightscreate Input file: chinadata.shp Queen contiguity Click Add ID Variable (using existing variable

29、does not work) Enter new variable name: Poly_ID Click Save to DBF ClickYes, its safe Click Create and name the file: ChinaData.gal A new file ChinaData.gal is saved in the folder with Check File: Go to ToolsWeightsPropertiesEnter name of weights fileHistogram (frequency distribution) showing number

30、of neighborsPolygons with zero neighbors are potential problems (4 in this case)Click on zero column and they are highlighted on map (Linking)Open table (TablePromote) and they are highlighted in tableBriggs Henan University 201021Format of .gal File.gal file is a .txt file: open with NotepadBriggs

31、Henan University 201022First line: 4 items: 0, Number of observations, filename, IDvariableAll subsequent lines are in sets of two:ID, number of neighbors List of neighbor IDsID, number of neighbors List of neighbor IDs0 35 ChinaData POLY_ID1 02 1303 625 14 11 6 5 44 523 9 6 5 35 630 14 13 9 4 3Hain

32、anMacau6.2 Calculate Morans I Calculate Morans I: SpaceUnivariate MoranVariable: Illiteracy Click OKSelect Weight: ChinaData.galClick OKMoran Scatterplot opens W_Illiteracy on vertical (Y) axis (neigbors) Illiteracy on X axis Morans I is .2047 Briggs Henan University 2010236.3 Statistical Significan

33、ce via SimulationCheck Statistical Significance via Simulation: Right Click on scatterplot and select OptionsRandomization Select 999 permutations Click Run for additional simulations and to check sensitivity of resultsIf p-value Univariate LISAVariable: Illiteracy Click OKWeights: chinadata.galClic

34、k OKPlace checks in top 2 boxes We discussed these maps in our last lecture 6.5 Saving Results of LISA AnalysisSave spatial lag and standardized (z scores) for variable analyzedRight-click Moran scatterplot and go to Save Results.Check the boxes you wantOptionally, change the default variable namesB

35、riggs Henan University 201026Save LISA scores, relationship type*, and probability level Right-click significance or cluster map and go to Save Results.Check the boxes you wantOptionally, change the default variable names*1: high-high, 2: low-low, 3: low-high, 4: high-lowTo permanently add the new v

36、ariables to the table, right-click on the table and go to Save Shape File As.6.6 puting Morans I for selected observations The Morans I slope and value can be puted for all observations excluding the ones selected:Right-click on Moran scatterplot and choose Exclude SelectedExclude selected observationsClick an individual observation or drag a box and Morans I is puted excluding selected observation(s)New value shown in red on top rightExclude ob