VisuallyComparingMaps.pptVIP

Spatial Data Mining  Practical Approaches for Analyzing Relationships Within and Among Maps Visually Comparing Maps Approach for Comparing Discrete Maps Coincidence Summary Results (Table 1) Proximal Alignment Results (Table 2) Approach for Comparing Map Surfaces Statistical Test Results (Table 3) Percent Difference Results (Table 4) Surface Configuration Results (Table 5) Visualizing Spatial Relationships Clustering Maps for Data Zones Evaluating Clustering Results Spatial Data Mining Spatial Data Mining  Practical Approaches for Analyzing Relationships Within and Among Maps * Berry Associates // Spatial Information Systems2000 S. College Ave, Suite 300, Fort Collins, CO 80525Phone: (970) 215-0825 Email: jberry@ …visit our Website at /basis “GIS technology is rapidly moving beyond mapping and spatial database management to analytical capabilities that assess spatial relationships within decision-making contexts” (JKB) Presented by Joseph K. Berry W.M. Keck Scholar in Geosciences, University of Denver But just how similar are the maps? …what proportion has the same classification? …where are they different? …where are they the same? and of course, your response should be objective and repeatable I bet youve seen and heard it a thousand times before ? a speaker waves a laser pointer at a couple of maps and says something like see how similar the patterns are. (Berry) (Berry) (Berry) (Table 1) (Berry) (Table 2) (Berry) …Statistical Tests of entire surface or partitioned areas (Berry) (Table 3) (Berry) …Percent Difference between two map surfaces (Table 4) (Berry) The two superimposed maps at the left side of figure show the normalized differences in the slope and aspect angles (dark red being very different). The map of the overall differences in surface configuration (Sur_Fig Index) is the average of the two maps. Note that over half of the map area is classified as low difference (0-20) suggesting that the two surface maps align fairly