selection • topological overlays • buffering

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 layers 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

floating-point (decimals)

integer (no 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

Analysis properties determine spatial properties for all newly created output grid layers

 Analysis properties • Working directory • Masking • Spatial extent of output • Cell size

 Once set, analysis property values stay set until changed

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

e.g. flow accumulation

Global functions apply a calculation based on all cell values

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

for zone 1: (53 + 57 + 33 + 78 + 31 + 12 + 32 + 9 + 9 + 33 + 76) = 423

zonal sum

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

raster layers operators

expression box

operator classes

Map Algebra arithmetic: Calculation = (Dem gt 500 and Dem lt 1000 )

Logical (Boolean) criteria

Grid analysis: Map algebra

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

select polygon field to define zones of cells

select grid layer containing variable to summarize

Summarizing zones

specify output select statistic to graph

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

row

laye

r (so

ils)

record layer (stands)

area measurements in map units

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 value is selected from input layer table

• output cells have the value of the closest input feature

“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