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ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 KEEP THIS TEXT BOX this slide includes some ESRI fonts. when you save this presentation,

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Presentation on theme: "ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 KEEP THIS TEXT BOX this slide includes some ESRI fonts. when you save this presentation,"— Presentation transcript:

1 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 KEEP THIS TEXT BOX this slide includes some ESRI fonts. when you save this presentation, use File > Save As > Tools (upper right) > Save Options > Embed TrueType Fonts (all characters) this will allow vector maps created with common ESRI symbols to show on computers that do not have ESRI software loaded a a a a a a ESRM 250/CFR 520 Autumn 2009 Phil Hurvitz Raster Analysis 2 1 of 42

2 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal Statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 2 of 42 Overview

3 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 3 of 42 Overview

4 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 ArcGIS can import rasters from many different generic raster data formats  ASCII raster file format  binary raster file format  USGS Digital Elevation Model (DEM) raster file format*  US DMA DTED raster file format 4 of 42 Importing data from generic raster files *common format; free for download

5 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 USGS DEMs are available online (free) 5 of 42 Importing data from generic raster files USGS source UW source

6 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 USGS DEMs are available online (free) 6 of 42 Importing data from generic raster files

7 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 7 of 42 Overview

8 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Generation of a complete surface from incomplete point samples Interpolation between and beyond individual sample points For estimating values at locations where actual measurements were not made 8 of 42 Creating surfaces from point samples

9 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Better estimation of surface value at locations near measured sample points Several different interpolation methods are available Assumption of gradual change of value across landscape “GIGO:” Garbage In, Garbage Out Advanced Kriging & geostatistics methods are also available in ArcGIS (but beyond the scope of this course) 8 of 42 Creating surfaces from point samples

10 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Points are interpolated to a surface 9 of 42 Creating surfaces from point samples continuous surface discrete sample points

11 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Two basic methods (spline and IDW) 10 of 42 Creating surfaces from point samples spline (minimized curvature) inverse distance weighting (local influence is strong)

12 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 11 of 42 Overview

13 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Finds adjacent cells of the same value Converts linear arrangement of raster cells to vector lines Creation of individual contours as simple graphics, or Creation of feature dataset of contours for entire raster layer User control of base contour and contour interval Why is this tool valuable? Few digitized contour line data sets exist for remote areas, but DEMs frequently do exist 12 of 42 Mapping contours

14 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Group of contours created as shapefile 13 of 42 Mapping contours new layer

15 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 14 of 42 Overview

16 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Defines zones of cells based on a group of integer cells or polygons with similar value Creates statistical summary of each zone Summary table is created Summary chart (optional) 15 of 42 Summarizing zones

17 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 “Zone” is a group of cells (or polygons) that have the same attribute value 16 of 42 Summarizing zones

18 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Summary table definition 17 of 42 Summarizing zones select polygon field to define zones of cells select raster layer containing variable to summarize specify output select statistic to graph (optional)

19 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Table and chart are created 18 of 42 Summarizing zones statistics from input raster based on polygonal zones

20 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 19 of 42 Overview

21 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Creates a “zonal intersection” of integer raster layers (similar to vector intersection) Output is a table 1st input layer creates records (1 record for each unique value) 2nd input layer creates fields (1 field for each unique value) Table values are map unit area measurements of combinations of zones Valuable technique for change detection 20 of 42 Cross tabulating areas

22 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 An example: ownership & forest type 42 Cross tabulating areas potential vegetation type

23 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Each ownership & vegetation class is quantified (remember all graphs come from tables) 42 Cross tabulating areas

24 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Cross-tabulation setup 21 of 42 Cross tabulating areas rows columns

25 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Output table 22 of 42 Cross tabulating areas row layer (soils) record layer (stands) area measurements in map units (e.g., 2933100 square feet)

26 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Combination of Kapowsin soil and mixed-redcedar = 2933100 ft 2 = 67.33 ac 23 of 42 Cross tabulating areas

27 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 24 of 42 Overview

28 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Raster Calculator is easy to use and gives rapid results Results may be as good as vector overlay depending on cell size & relative precision Multiple rasters can be simultaneously queried (whereas only 2 vector layers can be compared in vector overlay) Output represents cells that meet and do not meet query criteria 25 of 42 "Querying" across multiple raster layers (“Map Query”)

29 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Building Map Queries 26 of 42 "Querying" across multiple raster layers GUI query builder interface result is a new temporary raster

30 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Find cells where: 1.distance to streams < 300 ft and 2.elevation > 1500 ft and 3.timber volume > 60 mbf/ac 26 of 42 "Querying" across multiple raster layers

31 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Cells that meet all three criteria are identified (value = 1) 26 of 42 "Querying" across multiple raster layers

32 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 27 of 42 Overview

33 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 “Focal” statistical functions Moving “focus” (also known as “kernel”) window calculates statistics for all cells within the focus Output value is written to central cell (also known as “focal cell”) in the output raster Statistical functions: 28 of 42 Calculating neighborhood statistics Minimum Maximum Mean Median Sum Range Standard Deviation Majority Minority Variety

34 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Focal Standard Deviation 29 of 42 Calculating neighborhood statistics locations of greatest variation in elevation

35 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 High-pass filter (a focal process) 30 of 42 Calculating neighborhood statistics: high pass filter uses these coefficients on the kernel

36 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 High-pass filter finds edges 31 of 42 Calculating neighborhood statistics: high pass filter edges are higher in absolute value for the output grid

37 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 32 of 42 Overview

38 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Similar to buffering with vector data but with greater informational content Creates a continuous distance surface rather than a discrete bounded polygonal area (A vector buffer results in “inside/outside” whereas the distance surface gives measured distances) Distance measured from input layer features or raster cells 33 of 42 Calculating distance surfaces and buffers

39 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Distance from vector features 34 of 42 Calculating distance surfaces and buffers continuous distance value surface

40 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Limitation by maximum distance  Like a vector buffer but also with measured distance for each output cell 35 of 42 Calculating distance surfaces and buffers

41 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 36 of 42 Overview

42 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Defining territories based on proximity  Can be applied in analysis of competition Assigning proximity

43 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 “what territories are closest to a set of features?” 37 of 42 Assigning proximity output value is selected from input layer table output cells have the value of the closest input feature aka “Thiessen,” “Voronoi”

44 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a raster layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple raster layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources 38 of 42 Overview

45 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Raster  vector conversions are possible Always a loss or generalization of shape Support for point, line, polygon  raster in ArcGIS Avoid converting rasters that do not have large contiguous zones (e.g., DEMs) 39 of 42 Converting raster and vector data sources

46 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Convert raster zones to polygon feature data set 40 of 42 Converting raster and vector data sources: raster to polygon select conversion field, output name & folder polygon shapefile

47 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Convert raster zones to polygon shapefile 41 of 42 Converting raster and vector data sources: raster to polygon GRIDCODE field stores vector attribute

48 ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 1999-2009 Convert vector lines to raster zones 42 of 42 Converting raster and vector data sources: raster to polygon Value field


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