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Topic 4: Raster Data Analysis

Topic 4: Raster Data Analysis. Kang-tsung Chang Department of Geography University of Idaho Moscow, ID 83844-3021 E-mail: chang@uidaho.edu Fax: (208) 885-2855 Phone: (208) 885-6216. Chapter Outline 11.1 Introduction 11.2 Data Analysis Environment Box 11.1 How to Make a Mask Grid

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Topic 4: Raster Data Analysis

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  1. Topic 4: Raster Data Analysis Kang-tsung Chang Department of Geography University of Idaho Moscow, ID 83844-3021 E-mail: chang@uidaho.edu Fax: (208) 885-2855 Phone: (208) 885-6216

  2. Chapter Outline 11.1 Introduction 11.2 Data Analysis Environment Box 11.1 How to Make a Mask Grid 11.3 Local Operations 11.3.1 Local Operations with a Single Grid 11.3.2 Local Operations with Multiple Grids Box 11.2 Local Operations in ArcGIS 11.3.4 Applications of Local Operations 11.4 Neighborhood Operations Box 11.3 Neighborhood Operations in ArcGIS 11.4.1 Applications of Neighborhood Operations 11.5 Zonal Operations Box 11.4 Zonal Operations in ArcGIS 11.5.1 Applications of Zonal Operations

  3. 11.6 Distance Measure Operations 11.6.1 Physical Distance Measure Operations 11.6.2 Cost Distance Measure Operations Box 11.5 Cost Grid for a Site Analysis of Pipelines Box 11.6 Derivation of the Least Accumulative Cost Grid Box 11.7 Distance Measure Operations in ArcGIS 11.6.4 Applications of Distance Measure Operations 11.7 Spatial Autocorrelation

  4. Applications: Raster Data Analysis Task 1: Perform a Local Operation Task 2: Perform a Neighborhood Operation Task 3: Perform a Zonal Operation Task 4: Measure Physical Distances Task 5: Compute the Least Accumulative Cost Distance

  5. Raster Data • Public data • Satellite imagery including air photos • DEMs including global DEMs • Digital orthophotos (DOQ) • Digital raster graphics (DRG) • Graphic files (e.g., JPEG, BMP, TIFF)

  6. SpaceImaging: Shanghai, China

  7. QuickBird: Miami Beach, FL

  8. Elevation Zone Hillshade Data

  9. TIN created from LIDAR (light detection and ranging) Data Ground Elevation Canopy Elevation

  10. Orthophoto

  11. Digital Raster Graph (DRG)

  12. Raster Vector Data Conversion

  13. Raster Data Operations • Local Operations • Neighborhood Operations • Zonal Operations • Distance Measure (Global) Operations

  14. Local Operation • Local operations with a single grid • Local operations with multiple grids • Applications of local operation

  15. Arithmetic +, -, /, *, absolute, integer, floating-point Logarithmic exponentials, logarithms Trigonometric sin, cos, tan, arcsin, arccos, arctan Power square, square root, power

  16. a b A slope grid may be measured in percent (a) or in degrees (b). A local operation can be used to convert between the two measurement systems.

  17. Summary Statistics for Local Operations with Multiple Grids • Grids with numeric data: maximum, minimum, range, sum, mean, median, and standard deviation • Grids with categorical data: majority, minority, and number of unique values

  18. a b c d The combine operation sorts out the unique combinations of cell values in (a) and (b) and assigns a unique value for each combination in (c). The combination codes and their representations are shown in (d).

  19. Applications of Local Operations Local operations are perhaps most useful for GIS models that require mathematical computation on a cell-by-cell basis. The Revised Universal Soil Loss Equation (RUSLE) uses six environmental factors in the equation A = R K L S C P A logistic regression model for predicting favorable wolf habitat uses the equations Logit (p) = -6.5988 + 14.6189 R, and p = 1 / [1 + elogit(p)]

  20. Neighborhood Operations A neighborhood operation involves a focal cell and a set of its surrounding cells. The surrounding cells are chosen for their distance and/or directional relationship to the focal cell. Two common neighborhoods are a focal cell and its four immediate neighbors, and a focal cell and its eight adjacent neighbors in a 3-by-3 window

  21. a b The moving average method calculates the mean of cell values within a moving window and assigns the mean to the focal cell. In this illustration, the cell values in (b) are the moving averages of the shaded cells in (a) using a 3 x 3 moving window. For example, 1.56 in the output grid is calculated from (1 +2 +2 + 1 + 2 + 2 + 1 + 2 + 1) / 9.

  22. a b In this illustration, the cell values in (b) are derived for the shaded cells in (a) from a 3 x 3 neighborhood operation using the range statistic. For example, the upper left cell in the output grid has a cell value of 100, which is calculated from (200 – 100).

  23. a b In this illustration, the cell values in (b) are derived for the shaded cells in (a) from a 3 x 3 neighborhood operation using the majority statistic. For example, the upper left cell in the output grid has a cell value of 2 because there are 5 2’s and 4 1’s in its neighborhood.

  24. Applications of Neighborhood Operations An important application of neighborhood operations is data simplification. Neighborhood operations are common in image processing. Terrain analysis uses neighborhood operations to calculate slope, aspect, and surface curvature measures.

  25. Derivation of a Slope Map from an Elevation Grid

  26. Zonal Operations A zonal operation works with groups of cells of same values or like features. A zonal operation may work with a single grid or two grids. Given a single input grid, zonal operations describe the geometry of zones, such as area, perimeter, thickness, and centroid Given two grids in a zonal operation, one input grid and one zonal grid, a zonal operation produces an output grid, which summarizes cell values in the input grid for each zone in the zonal grid.

  27. This illustration shows two large watersheds and their zonal geometric measures. The cell resolution is 2000 meters; therefore, the areas are measured in square meters, the perimeters in meters, and the thickness measures in meters. The centroid of each zone is shown by an x.

  28. Zonal Grid Input Grid The zonal operation in this illustration uses the zones of 1, 2, and 3 in (a) and the cell values in (b) to calculate the zonal means of 2.17, 2.25, and 4.17. The output grid is shown in (c). Output Grid

  29. Applications of Zonal Operations Zonal operations with a single grid produce area, perimeter, thickness, and centroid that are part of a large group of geometric measures useful for studies of landscape ecology. Zonal operations with two grids are useful in generating descriptive statistics for comparison purposes.

  30. Distance Measure Operations • Physical distance measure operations • Cost distance measure operations • Applications of distance measure operations

  31. An example of continuous distance measures from a stream network

  32. An example of assigning each cell to its closest stream (allocation)

  33. Cost Grid A cost distance measure operation uses the cost or impedance to traverse each cell as distance unit, and requires a cost grid defining the cost or impedance to move through each cell. The cost for each cell in the cost grid is often the sum of different costs.

  34. How to Prepare a Cost Grid A site analysis of a pipeline project must consider the construction and operational costs. Some of the variables that can influence the costs include the following: • distance from source to destination; • topography, such as slope and grading; • geology, such as rock and soils; • number of stream, road, and railroad crossings; • right-of-way costs; and • proximity to population centers. In addition, the site analysis should consider the potential costs of environmental impacts during construction and liability costs that may result from accidents after the project has been completed. Environmental impacts of a proposed pipeline project may involve the following: • cultural resources; • land use, recreation, and aesthetics; • vegetation and wildlife; • water use and quality; and • wetlands.

  35. The cost distance of a lateral link is the average of the costs in the linked cells, for example, (1 + 2) / 2 = 1.5. The cost distance of a diagonal link is the average cost times 1.4142, for example, 1.4142 x ((1 + 5) / 2) = 4.2.

  36. Using the grid with two source cells (a) and the cost grid (b), this illustration shows the cost distance for each link (c), and the least accumulative cost distance from each cell to a source cell (d).

  37. Direction measures in a direction grid are numerically coded. The focal cell has a code of 0. The numeric codes 1 to 8 represent the direction measures of 90°, 135°, 180°, 225°, 270°, 315°, 360°, and 45° in a clockwise direction. This illustration shows the least cost path (a) and the allocation grid (b).

  38. Applications of Distance Measure Operations Physical distance measure operations are like buffering around vector-based features and have many applications. Cost distance measure operations are commonly used for site analysis of roads and pipelines to find the least accumulative cost path. But they can also be applied to other types of movement.

  39. Thank You!

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