1 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal Statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

2 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

3 Importing data from generic raster files ArcGIS can import grids from 4 different generic raster data formats –ASCII raster file format –binary raster file format –USGS Digital Elevation Model (DEM) raster file format* –US DMA (Defense Mapping Agency) DTED (Digital Terrain Elevation Data) raster file format *common format; free for download from USGS

4 Importing data from generic raster files USGS DEMs are available online (free) USGS source

5 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

6 Creating surfaces from point samples Generation of a complete surface from incomplete point samples Interpolation between and beyond individual sample points Better estimation of surface value in locations near sample points Several different interpolation methods available Assumption of gradual change of value across landscape

7 Creating surfaces from point samples Points are interpolated to a surface Contin uous surface discrete sample points

8 Creating surfaces from point samples Two basic methods (spline and IDW) spline (minimized curvature) inverse distance weighting (local influence is strong)

9 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources_

10 Mapping contours Finds adjacent cells of the same value Converts linear arrangement of raster cells to vector lines User control of base contour and contour interval Few digitized contour line data sets exist for remote areas

11 Mapping contours Group of contours created as shapefile new layer

12 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

13 Defines a zone of cells based on a group of integer cells or polygons with same value Creates statistical summary of zone Summary table is created Summary chart Summarizing zones

14 “Zone” is a group of cells (or polygons) that have the same attribute value Summarizing zones

15 Table and chart are created statistics from input grid based on polygonal zones Summarizing zones

16 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

17 Cross tabulating areas Creates a “zonal intersection” of integer grid 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

18 Cross tabulating areas Output table row layer (soils) column layer (stands) area measurements in map units

19 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

20 "Querying" across multiple grid layers (“Map Query”) 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 grids 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

21 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

22 Calculating neighborhood statistics “Focal” statistical functions Moving focus window calculates statistics for all cells within focus Output value is written to central cell in output grid Statistical functions: Minimum Maximum Mean Median Sum Range Standard Deviation Majority Minority Variety

23 Calculating neighborhood statistics Focal Standard Deviation locations of greatest variation in elevation

24 Calculating neighborhood statistics: high pass filter High-pass filter (focal process)

25 Calculating neighborhood statistics: high pass filter High-pass filter finds edges edges are higher or in absolute value

26 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

27 Calculating distance surfaces and buffers Similar to buffering with vector data Creates a continuous distance surface rather than a discrete bounded polygonal area Distance measured from input layer features or grid cells

28 Calculating distance surfaces and buffers Distance from vector features continuous distance value surface

29 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

30 Assigning proximity “what territories are closest to a set of features?” output cells have the value of the closest input feature “Thiessen,” “Voronoi”

31 Overview Importing data from generic raster files Creating surfaces from point samples Mapping contours Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”) Cross tabulating areas "Querying" across multiple grid layers Calculating neighborhood statistics Calculating distance surfaces and buffers Determining proximity Converting raster and vector data sources

32 Converting raster and vector data sources Raster  vector conversions are possible Always a loss or generalization of shape Support for point, line, polygon  grid in ArcGIS Avoid converting grids that do not have large contiguous zones (e.g., DEMs)

33 Converting raster and vector data sources: grid to polygon Convert grid zones to polygon shapefile polygon shapefile

34 Converting raster and vector data sources: grid to polygon Convert grid zones to polygon shapefile GRIDCODE field

35 Converting raster and vector data sources: grid to polygon Convert vector lines to grid zones Value field