1. Raster Analysis

2. Learning Objectives Develop an understanding of the principles underlying lab 4 Introduce raster operations and functions Show how raster analysis can be applied to topographic surfaces

3. Raster Data

4. Derived Data By taking rasters and operating on them we can create additional data inRaster * 2 = outRaster Slope(inRaster) = outRaster

5. Creating New Data With Rasters Digital Elevation ModelSlope Model

6. Raster analysis Typically 4 steps Base data Derived data Classified data Combined data

8. Reclassifying raster data One reason is to set specific values to NoData to exclude them from analysis. Another reason is to assign values of preference, priority, sensitivity, or similar criteria to a raster.

10. Operations Boolean (AND, OR, NOT, XOR) Arithmetic (+,-,*,/) Mathematical (trig, log, etc.) Logical (,=,<>,etc.) Overlay Derivation Transformation

11. Boolean (AND, OR, NOT, XOR) Boolean And Boolean Or

12. Arithmetic (+,-,*,/)

14. Raster Calculator

15. Working with NoData Similar to logical values, NoData (Null) values also influence the evaluation of expressions. This special value indicates that there is no information associated with the cell. In general, a Map Algebra expression will return NoData for a cell if any of the corresponding input cells have NoData.

16. Functions Local Global Focal Zonal

17. Local Very simple Operate on each cell individually Arithmetic and boolean are examples of Local functions

18. Global Perform operations based on an entire input grid E.g. Global statistics

19. Focal Evaluates a new grid by summarizing statistics in the neighborhood around each cell. Filters

20. Low-pass filter Also referred to as a mean filter

21. Low-pass filter DEMLow-pass filter

22. High-pass Filter Also referred to as edge enhancement

23. High-pass filter DEMHigh-pass filter

24. Additional Filters

25. Zonal Operations based on zones of like values in a grid Zonal geometry Zonal stats

26. Zonal InputOutput

27. Recap

28. Distance Euclidean Rectilinear Weighted

29. Weighted Distance Sometimes referred to as cost path or travel cost

30. Surface Analysis Derivatives Slope Aspect Hillshade Visibility - Viewshed - Line of Sight Feature Interpolation - Interpolate Shape - Interpolate Poly To Patch - Surface Length - Surface Spot - Contour Volume - Surface Volume - Cut Fill - Surface Difference - Polygon Volume - Extrude Between

31. Slope: steepness Aspect: direction of steepest slope Hillshade: steepness and direction relative to light source

32. Slope Slope is calculated as the maximum rate of change in values between each cell and its neighbors. Slope may be expressed as either degrees (e.g., 45 degrees) or percent (e.g., 50%). Measures of slope in degrees can approach 90 degrees and measures of slope in percent can approach infinity.

33. Aspect The cell values in an aspect grid are compass directions ranging from 0 to 360. North is 0 and in a clockwise direction, 90 is east, 180 is south, and 270 is west. Input grid cells that have 0 slope (flat areas) are assigned an aspect value of -1.

34. Hillshade Hillshading creates a hypothetical illumination of a surface by setting a position for a light source and calculating an illumination value for each cell based on the cell's relative orientation to the light, or based on the slope and aspect of the cell.

35. Viewshed The viewshed identifies the cells in an input raster that can be seen from one or more observation points or lines. Each cell in the output raster receives a value that indicates how many observer points can see the location.

36. Line of Sight Distance Elevation 075150225300345 Observer 156 181 206 231 Target

37. Volume Below Plane

40. Summary Most of the power of the Spatial Analyst is found within Map Algebra. The Raster Calculator is your friend. You can construct a extremely complex Map Algebra expression using this interface