Review- vector analyses Selection Topological Overlays Buffering

Selection Selecting points near a line (proximity) Selecting adjacent features (proximity) Selecting lines within polygons (containment) Selecting polygons that contain lines (overlap) Selecting points within polygons (containment) Selecting polygons that contain points (overlap) Selecting polygons that overlap polygons (overlap)

Types of overlays Union Clip Identity Intersect Update Erase

Clipping… an example

Clipping… an example

ArcGIS does NOT automatically update geometry fields for shapefiles

Raster Analysis

Overview Grid layers Setting grid layer and analysis properties Grid function types Performing grid analysis Map Algebra More grid analyses

Grid layers

Grid layers The grid layer is the format ArcInfo uses for raster data.

Grid layers A grid layer is a rectangular grid of square cells

Grid layers Not all raster datasets are grid layers reflectance values

Grid layers Cells have numeric values

Grid layers Grid layers are suited for representation of phenomena that vary gradually over space such as elevation, wind speed and direction, or slope

Grid types integer (no decimals) floating-point (decimals)

Grid types Integer grids can have value attribute tables (VATs), floating point grids do NOT

Grid types Integer grids with: a range of values < 100,000 and < 500 unique values will have attribute tables

Displaying grid layers Legends can be altered like other layers

Identity tool Individual cell values can be identified

Queries Integer grids can be queried in the same way as vector layers (select by attribute)

Setting grid layer and analysis properties

Setting analysis properties Working directory Masking Spatial extent of output Cell size Once set, analysis property values stay set until changed Analysis properties determine spatial properties for all newly created output grid layers

Analysis extent Analysis extent sets the spatial properties for output of analyses Rectangular area

Analysis extent Be careful about setting extent; it may cause poor grid-to-grid registration

Cell size Analysis cell size sets the grid cell size for output of analyses Use a consistent cell size for analysis of multiple grid data sets small cells → larger files small cells → longer processing

Masking Analysis mask defines spatial extent of output grids Mask can be any shape (as opposed to the Analysis Extent)

Grid function types

Grid function types Local Global functions Zonal functions Focal functions

Local functions Local functions apply an independent calculation to all input grid cells local sine e.g. sin(12) = -0.537

Global functions Global functions apply a calculation based on all cell values e.g. flow accumulation

Zonal functions Zonal functions apply one calculation to all input grid cells within each zone Zones are defined as a group of cells having the same value Regions are groups of contiguous cells having the same value

Zonal functions Zonal functions apply one calculation to all input grid cells within each zone zonal sum for zone 1: (53 + 57 + 33 + 78 + 31 + 12 + 32 + 9 + 9 + 33 + 76) = 423

Focal functions Focal functions apply one calculation to all input grid cells within a focal distance focal mean (27 + 8 + 22 + 16 + 21 + 16 + 6 + 44 + 8) / 9  18.7

Performing grid analysis

Grid analysis: calculations across multiple grids Multi-grid analyses are possible because of spatial registration multiple grid layers share the same X, Y coordinate space cell values are calculated across multiple grid layers to create a single output grid layer

Grid analysis Spatial Analyst toolbar ArcToolbox tools Scripting Command Line

Spatial Analyst toolbar Raster calculator

Spatial Analyst extension

Map Algebra

Grid analysis: Map algebra arithmetic expressions output_data_set = input_grid1 operator input_grid2 . . . slp_dem = slp_grid * dem algebraic functions output_data_set = function (input_data_set[s] {,arguments}) slp_grid = slope (dem, percentrise)

Map algebra can be calculated with the Raster Calculator operator classes operators raster layers expression box

Grid analysis: Map algebra Map Algebra arithmetic: Calculation = (Dem gt 500 and Dem lt 1000 ) Logical (Boolean) criteria

Grid analysis: Map algebra 0 = false 1 = true

More grid analysis 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

Calculating summary attributes for polygon features using a grid layer (“Zonal statistics”)

Summarizing zones Summarizes groups of cells based on integer cells or polygons with similar value Creates statistical summary of zone Summary table Summary chart

Summarizing zones

Summarizing zones select polygon field to define zones of cells select grid layer containing variable to summarize select statistic to graph specify output

statistics from input grid based on polygon zones

Ecological Applications: Vol. 17, No. 1, pp. 18–33. INFLUENCE OF ENVIRONMENT, DISTURBANCE, AND OWNERSHIP ON FOREST VEGETATION OF COASTAL OREGON Janet L. Ohmann, Matthew J. Gregory, and Thomas A. Spies

Cross tabulating areas

Cross tabulating areas Creates a “zonal intersection” of integer grid layers or grids and polygon vectors (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

Cross tabulating areas Cross-tabulation setup rows columns

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

Cross tabulating areas Identifying fields

Cross tabulating areas

Cross tabulating areas

"Querying" across multiple grid layers (“Map Query”) Raster Calculator is easy to use and gives rapid results Multiple grids can be simultaneously queried (vector overlay only allows 2) Output represents cells that meet and do not meet query criteria (T or F)

"Querying" across multiple grid layers

Building Map Queries

Calculating neighborhood statistics

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

Focal Standard Deviation locations of greatest variation in elevation

Calculating distance surfaces and buffers

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

Distance from vector features continuous distance value surface

Create a “graded” buffer by setting a max distance

Determining proximity

Assigning proximity Defining territories based on proximity

Assigning proximity output cells have the value of the closest input feature output value is selected from input layer table “Thiessen,” “Voronoi”

Converting raster and vector data sources

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

homework Read “Raster Analysis 2” & “Data Conversion” & “Model building” Finish assignment 5 Start assignment 6

Ecological Applications: Vol. 17, No. 1, pp. 18–33. INFLUENCE OF ENVIRONMENT, DISTURBANCE, AND OWNERSHIP ON FOREST VEGETATION OF COASTAL OREGON Janet L. Ohmann, Matthew J. Gregory, and Thomas A. Spies