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CSS 4200 GIS Fall 2008 Problem Set Terrain Derivatives Spatial Interpolation Accuracy Assessment Land Cover Change Global Positioning System (1a) Compute slope gradient in percent (%) and arc-degrees (o) for the central cell of the following matrix of elevation values (Use Ritter’s algorithm in lecture notes or Bolstad’s algorithm in the text book for slope gradient only). Assume the cell (grid, raster) size is 100 meters (c =100). Z 115 Z 110 Z 100 Z 125 Z 115 Z 105 Z 130 Z 120 Z 115 (1b) Compute slope azimuth (in arc-degrees) for the central cell of the matrix of elevation values shown in #9, above (use Ritter’s algorithm in lecture notes).
CSS 4200 GIS Fall 2008 (2) Estimate the mean annual temperature for location “T,” as shown in the illustration below, using Thiessen polygons and Inverse Distance Weighting (IDW). Use Gages #38, #48, and #50 for Thiessen and IDW. Simply create (draw) the Thiessen polygons in the illustration below, and calculate IDW (n=1, i=3) using the example in Bolstad textbook (Chapter 12, p.447-448). Station_ID Gage # UTMe UTMn Zone Elev, m Temp, oC 112036 138 343385 1269813 Weyna Dega 1654 20. 111006 39 350940 1309333 Weyna Dega 1786 19. 111005 38 360529 1327640 Weyna Dega 1795 19. 111009 42 389007 1332580 Weyna Dega 1877 19. 111014 47 350649 1293932 Weyna Dega 2072 18. 111017 50 365179 1286958 Weyna Dega 2271 17. 112040 142 398015 1284633 Weyna Dega 2385 16. 112039 141 394528 1284633 Weyna Dega 2390 16. 111013 46 399759 1308752 Dega 2583 15. 111015 48 407314 1304974 Dega 2772 14. “T” location: 385500 (UTMe) 1303000 (UTMn)
“T”
CSS 4200 GIS Fall 2008 (4) Construct a land use/land cover change matrix from the data tabulated below derived from a cross-tabulation between two maps (“Tabulate Areas” in ArcMap). Compute the proportion (in percent) of land which did not change land use or cover type during T 0 and T 1. Compute and tabulate the percent change by land cover type in the table below the matrix. Describe important land cover changes and those which do not seem reasonable. To what do you attribute the unreasonable (or nonsensical) transitions? Transition: T 0 - T 1 Area, ha For - For 2500 For - Urb 500 For - Wat 150 Urb - For 75 Urb - Urb 1500 Urb - Wat 100 Wat - For 50 Wat-Urb 10 Wat-Wat 1050 Land Cover Change Matrix: Land Cover Change Table: Land Cover Type T 0 T 1 Percent Change Total:
CSS 4200 GIS Fall 2008 (5) Compute the root mean square error (RMSEx,y) associated with the three GPS- acquired points below (#138, #141, #142). Refer to Bolstad, Chapter 14 (equations 14.1 and 14.2) and use Excel to facilitate the calculations. Assume “T” is the true location (“benchmark”) from the National Geodetic Survey. This exercise is useful for assessing the accuracy and precision of your GPS instrument. Though their location and coordinate values are not always known to you, benchmarks can provide a good estimate of the “true” position on the Earth’s surface. By locating a benchmark near your study area or region and accessing the coordinate information for that benchmark on-line, take three or more measurements at the benchmark, then compute the RMSEx,y of those positions acquired by your GPS instrument. GPS # UTMe UTMn 138 340500 1200800 141 340530 1200795 142 340505 1200790 “T” 340520 1200795 RMSE (in meters) =
“T”
