Suitability Analysis in Raster GIS

Combining Multiple Maps

The Challenge Thus far

Single or Dual Factor Overlay Analyses i.e. Land Cover on Private Land

Biophysical Analyses with Algebraic Formulas i.e. RUSLE

Landscape Planning Dozens to hundreds of spatial factors Factors have “apples and oranges” characteristics Combinations must reflect social values, not just (bio)physical processes

“Best” for industrial development – from whose perspective? Therefore

“Suitability Analysis” is not objective - must typically be vetted by experts If experts are not GIS experts (i.e. local stakeholders), suitability factors and

their combination must be visually explained “Weighting and rating” is a key opportunity for public deliberation

Suitability Analysis

General purpose To rank potential sites according to suitability for a

proposed type of activity

Requirements A set of “factor” or criteria maps, organized to rate

sites relative to one or more characteristics A technique for appropriately combining factors

Types of Criteria Absolute

Frequently hard-edged Often include property ownership/management zones Often involve legal standards

Relative Typically “fuzzy” edged

E.g. “proximity to X” where closer = better, but no absolute distance known in advance

Often involved in trade-offs where values ranges come from specific data within a place Criterion 1 = “Low rent” and criterion 2 = “close to school”

Suitable For Whom?

Suitability models have a “point of view” Audience can be human

“Affordable housing” Best sites for High-end commercial

Audience can be environmental Best habitat for black bear Most suitable multispecies conservation areas

Can be implicit or explicit But better to be explicit where possible

Common Units

How do you “combine” a map representing “meters to nearest road”

Units = meters with another representing “land cost”?

Units = dollars

Short Answer: find or create common units Easiest: likert scale “preference” units

A range of values: 1 to 5, or 1 to 9 Polar opposites on both sides of range

i.e. “Best”/”Worst”, “Most Suitable”/”Completely Unsuitable”

Cautions with Likert Scales Consistent Application

With multiple factors, must make sure that scale consistently applied example analysis: want to be near streams and far from roads,

using 1..9 with 9 = best Calculate distance to streams, distance to roads Reclassify stream distance to preference units

Closest = 0 distance = 9 Reclassify road distance to preference units

Closest = 0 distance = 1 In other words, may need to “flip” values when reclassifying

Doesn’t really avoid scaling issues, just defers Sensitivity and range in price/distance may be different Often what’s needed from initial analysis is “range of the possible”

Automating Analyses with ModelBuilder

Overview

Why Use ModelBuilder? ModelBuilder Basics Common ModelBuilder Problems Advanced ModelBuilder

Why Use ModelBuilder?

An automation tool… But comes with some startup overhead Most useful in two circumstances

Documents models & their parameterization Allows experimentation with model parameters –

particularly for “weighting and rating” Common Types of Models

ETL – Extract, transform and convert raw data Suitability – Building attractiveness maps

ModelBuilder Basics

Basic idea is that of a “dependency diagram” User specifies inputs, processing and outputs If inputs change, system repeats intermediate operations

as needed Diagram has three kinds of elements

Inputs Geoprocessing Operations Outputs

Output from one operation can be used as input to an other, allowing “chaining”

ModelBuilder Setup

Rather obscure to start…implemented as a custom toolbox tool Open toolbox panel Create empty toolbox

Right mouse on Toolboxes, select New Toolbox Create empty model

Right mouse on new Toolbox, select New Model Then populate model by drag and drop

Of data layers from map table of contents Of geoprocessing operations from the toolbox

Finally, wire data and processing boxes together

Example: Simple MB Model Goal

Create a factor map expressing simple proximity to residential landuse where output is classed from 1..9

Method Create new model Select residential landuse from San Miguel Parcels database Add Euclidean distance geoprocessing operation Connect landuse (input) to distance (process), specifying new grid (output) Run Add Reclass Operator Connect output grid of distance operator to input of reclass, specifying new

output grid Run again

Review of Simple Model Benefits

Multiple logical steps encapsulated in a single step Model Logic Recorded in Diagram Model Parameters Recorded

Problems / Caveats Default is not to show results… Model as Created is 100% specific to particular data

paths/locations on disk Model Saving Bizarre.. Default operation names make no sense to end users Spatial Analyst Toolbar Options do *not* inherit

Showing Results

Simple, but not Obvious Right Mouse on Output -> Add to Display If at first you don’t succeed, try toggling again

Saving / Finding Models

By default, models saved in “My Toolboxes” folder Main menu Tools->Options->My Toolboxes Default is C:\Documents and Settings\(Username)

\Application Data\ESRI\ArcToolbox\My Toolboxes Easiest to find in ArcCatalog/My Toolboxes Can “Add Toolbox” stored on disk

Making Models Generalizable Running Models

Can Double Click on Models in Toolbox Panel By default, not too useful, because no user control of

outputs

Generalizing Models By default, models only use exact data originally specified To make a model into a true “tool” need to specify which

inputs / outputs are variable parameters Right mouse on input or output Select “Parameter” (toggle)

After Parameters are set, double clicking brings up user dialog

Making MB Diagrams Legible

All elements can be “renamed” from right mouse menu Rename layers if necessary to clarify Explain intent of geoprocessing operations

i.e. Isolate Residential Landuse instead of reclass1 If Desired, change diagram properties

Square – Circle – Square Box Background Colors If you need better quality, export diagram…

Environment Variables in MB

Note Spatial Analyst “Options” settings not inherited Must explicitly specify for MB Two options

Can do once for all toolboxes (recommended) RM Top Toolbox->Environment Settings

General Settings -> Extent Raster Analysis Settings -> Cell Size

Can do once for each model

Model 2: Weighted Overlay

Goal: To Create an Attractiveness Model with ability to

“Weight” factors

Method: Create separate ModelBuilder models for each

factor Nest models into master MB model Combine with weighted overlay

Model 2 Implementation

Factor 1: Proximity to Residential Factor 2: Proximity to Ski Slopes

Created by copying and pasting factor 1 model and adjusting inputs and outputs

Weighting Factor 1 = 2X Factor 2 Use Spatial Analyst Weighted Overlay tool