Raster Data 1
Vector Data Review discrete objects geometry = points by themselves connected lines closed polygons attributes linked to feature ID explicit location every point has coordinates 2
Fields in GIS continuous f(x, y) so how represent geometry? attributes? location? 3
Approximating Fields Point set regular irregular Grid Polygons TIN Contours 4
Sampled Fields: Rasters Divide (part of) the world into square cells Register the corners to the Earth Represent discrete objects as collections of one or more cells Represent fields by assigning attribute values to cells More commonly used to represent fields than discrete objects 5
Characteristics of Rasters Cell size defines level of spatial detail all variation within cells is lost for given area: cell size #cells data volume Cell value characteristic of spatial phenomenon at cell location ArcGIS: integer or floating-point assignment scheme average over cell total within cell commonest value in cell value at cell s central point 6
Characteristics of Rasters (cont d) Bands (channels) single multiple bands e.g. red,green,blue color image Implicit geometry location of any cell can be calculated from grid location cell size Spatial reference map implicit external coordinates e.g. in a map projection 7
Raster Datasets Name Structure cells aka pixels columns rows Value attribute key zone NoData ignored or propagated 8
Raster Attributes Cell value attribute table row count (always) anything else 9
Raster Coordinates left left 10
Raster Examples USGS 1-meter DOQ digital orthophoto quadrangle USGS 1:24000 DRG digital raster graphic scanned from 7.5 topo 11
Vector Raster Conversion Rasterize = cells that intersect feature Vectorize = outline contiguous region 12
Note: Distance vs Buffering Buffer: discrete Distance: continuous 13
Feature Representation in Rasters: Sub-pixel Features Coarsened 14
Feature Representation in Rasters: Large Features Blurred Tree represented as varying values of treeness, instead of as a crisp feature 15
Raster Operations in order of increasing #input cells contributing to 1 output cell Local Focal aka neighborhood Zonal Global 16
Local Operations out(xi, yj) = f(in(xi, yj)) Neighbors don't influence Examples reclassify select min/max Think of as: Solve for all unique cell values; then reclassify 17
Local Operation Example: 1 Input Reclassify (change values using lookup table) IN OUT 0 10 1 50 2 100 4 75 18
Local Operation Example: d = mean(a, b, c) shaded = NoData NB: NoData in any input NoData in output Multiple Inputs 19
Extent restrict processing to rectangular subset explicit: (xmin, ymin, xmax, ymax) implicit: dataset bounding box 20
works with features, too 21
Mask Restrict processing to coincident defined cells i.e. anything except NoData 22
Extract extract by polygon extract by mask 23
Focal (Neighborhood) Operations out(xi, yj) = f(in(xk, ym) k,m near i,j) single cell and its neighbors Examples smooth sharpen noise suppresion Think of as weighted sum or sort and pick 24
Neighborhood Types Four common neighborhood types rectangle circle annulus wedge (x = focal cell) 25
Focal Operation Example: Mean b = 3x3 mean (a) e.g. 2.11 = (2+2+2+2+1+3+2+2+3) / 9 26
Zones Zone = all cells with same value 27
Regions Region = contiguous cells with same value 28
Zonal Operations out(xi, yj) = f(in(xk, ym) k,m zone(xk, ym) = zone(xi, yj)) like focal, but uses zone for neighborhood replace cell value with some property of its neighbors in zone it overlaps 29
Zonal Operations (cont'd) ArcGIS supports majority, median, minority maximum, range, minimum sum, mean, standard deviation variety (# distinct values) Examples forest zone species variety elevation zone mean snow depth 30
Zonal Operation Example: Zonal Mean c = zonal mean (a, zone b) e.g. 2.17 = mean(zone 1: {1, 1, 2, 2, 4, 3}) 31
Global Operations out(xi, yj) = f(in(xk, ym) k,m) each output cell depends on all input cells can be computationally intensive Examples distance variogram 32
Global Operation Example: Re: nearest source cell: value distance direction Euclidean Allocation 33
Figure Credits Introduction to Geographic Information Systems, 4 th ed. ISBN 978-0-07-305115-2 ArcMap Help Modeling Our World. ISBN 1-879102-62-5 Geographic Information Systems and Science, 2nd ed. ISBN 978-0470870013 ArcGIS 9: Using ArcGIS Spatial Analyst 34