ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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)

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

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

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

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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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”)

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, “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

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

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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, “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”

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

ESRM 250 & CFR 520: Introduction to GIS © Phil Hurvitz, 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

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

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