Raster GIS applications
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1 Raster GIS applications Columns Rows Image: cell value = amount of reflection from surface DEM: cell value = elevation (also slope/aspect/hillshade/curvature) Thematic layer: cell value = category or measured value - In all cases, there is one value per cell (in each layer) Raster data tools -> histogram example Frequency (or area) plotted against value 1
2 GIS theme layers Integer and Floating point (decimal) data values Integers a Value Attribute Table (VAT) contains the number (count) of each value Floating point (decimals) No VAT. (too many different values). an information query will give the cell value Converting real values to integers e.g. DEM elevations - result from topo to raster interpolation Raster Calculator: Int ( dem ) 2
3 Converting decimal to integer: (map algebra-> raster calculator ) - creates a value attribute table - remove clutter detail (false precision) Raster Calculator e.g. to find all southerly aspects > 1500m 3
4 4
5 Other raster formats (easier for Transfer and data exchange) IMG Erdas Imagine (remote sensing) JPG also needs a.jpgw file (georeferencing) TIFF also needs a.tfw /.aux or.wld (world file) GeoTIFF data and georeferencing in a single file X, Y This cat has no.tfw or.jpgw file.. Groups of Raster operations Local: Operations done on cell by cell basis Neighborhood: Operations performed using an adjacent group of cells e.g. 3 x 3 Zonal: Operations performed using zones (groups of cells with the same value) 5
6 a. Local operations - overview Computes output cell values as a function of the input cell values Can use single or multiple rasters Common uses: reclassification and overlays Local Operations Reclassification (single raster) a new value is given to a range of values (or to a single old value) 6
7 e.g. DEM hypsometric layers Analysing by topographic layer range or for display Reclassification Applications Simplification - creating groups for analysis Replace values based on new information Create common scales for ranking data values (e.g. creating suitability classes) 7
8 GEOG300 project landslide susceptibility landslide factor 8
9 Local Operations Multiple Rasters Operation: add raster 1 and raster 2 cell values to produce an output raster with the summed / difference cell values Applications: change detection studies (subtraction) - predicting habitats favorable for wildlife species 9
10 Least Cost paths: Road building, human traffic, wildlife corridors Cost surfaces: least cost path between cut forest stand and sawmill 10
11 Algebra examples (for a stack of grids) Add, subtract, divide, multiply Maximum, minimum Mean, variance GEOG300: Avalanche project: Wells, BC Avalanche factor based on - per pixel: (according to published model) Elevation factor e.g m > Aspect 0.4 to 2.0 Plan/profile curvature Slope 0 (flat, very steep) to 2.0 (35-45 degrees) Land cover type (densely treed to bare rocks) 11
12 0-15 Low Medium High Local Operations Animation umulative%20pine%20killed%20-%201999%20to% gif Trend and modelling: animation showing the impact of the MPB on British Columbia from the years , and a projection from
13 b. Neighborhood Operations Operation: Summation (including value of focal cell) Neighborhood size: 3 x 3 rectangle e.g. to establish available food supply for wildlife Neighborhood Operations Summation (including value of focal cell) Other common applications: Data simplification (smoothing) Terrain analysis (local relief / roughness) Site selection 13
14 c. Zonal Operations Involves groups of cells with the same values or similar features (zones) e.g. -> number of plant types in 3 Different zones Lab example: min /max elevation by forest cover type (polygons as zones) 14
15 Zonal Histogram for land use zones and classified slope values Summary of raster analysis in Spatial Analyst Local/neighbourhood/zonal analysis Map Algebra raster calculator Surface Interpolation and Analysis Watershed/ Viewshed Analysis Distance and Proximity Analysis Resampling / Reclassifying 15
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