Raster GIS applications Columns

Transcription

1 Raster GIS applications Columns Rows Image: cell value = amount of reflection from surface Thematic layer: cell value = category or measured value - In both cases, there is only one value per cell (in a layer) Raster data tools -> histogram example 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 Select by Attribute -Works with raster data ONLY for integers -True for other options (see help) 2

3 Converting decimal to integer: Spatial Analyst (INT) - create a value attribute table - remove clutter detail (false precision) Raster Calculator 3

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5 ESRI GRID formats Other raster formats (easier for Transfer and data exchange) IMG Erdas Imagine (remote sensing) JPG also needs a.jpw file (georeferencing) TIFF also needs a.tfw or.aux or.wld (world file) GeoTIFF georeferencing embedded in a single file 5

6 3 types of Raster operations Local: Operations performed on a cell by cell basis Neighborhood: Operations performed using an adjacent group of cells Zonal: Operations performed using zones (groups of cells with the same value) a. Local operations - overview Cell by cell operations Computes output cell values as a function of the input cell values Can use single or multiple rasters Common uses: reclassification and overlays 6

7 Local Operations Reclassification (single raster) a new value is given to a range of values (or to a single old value) Reclassification Applications GIS! -> 7

8 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) Local Operations Multiple Rasters Operation: add raster 1 and raster 2 cell values to produce an output raster with the summed cell values Applications: change detection studies; predicting habitats favorable for wildlife species 8

9 Algebra examples (for a stack of grids) Add, subtract, divide 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) 9

10 0-15 Low Medium High Local Operations Animation Trend and modelling: animation showing the impact of the MPB on British Columbia from the years , and a projection from

11 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) Site selection 11

12 c. Zonal Operations Involves groups of cells with the same values or similar features (zones) Can be used with a single raster or with two rasters e.g. -> number of plant types in 3 Different zones Lab: min /max elevation by forest cover type (polygons as zone layer) 12

13 Exotic GIS query: Zonal Thickness Single Raster Example Answers the question: How far can you run into a forest at its deepest point before you are running out of it? Raster Analysis (Spatial analyst manual) Boston (Harvard) example: where to find the best places for (snow) sledding, based on : - available parks and slopes, accessibility to: - university, - public transport, - donut shops and - views of downtown landmarks 13