Let’s pretty it up!

Border around

project area

Everything else is hardly noticeable… but it’s there

Big circles… and semi-

transparent

Color distinction

is clear

Spatial Analysis

Spatial Analysis

• Spatial analysis refers to the formal techniques to conduct analysis using their topological, geometric, or geographic properties.

• In a narrower sense, spatial analysis is the process of analyzing geographic data.

• Types of spatial analysis you have already been doing:– Buffering– Select by location

• Layers can be overlaid - placed one over the other based on a shared geographic reference – allows analysis of the relationships between layers

• Raster analysis is one method of Spatial

Analysis.

Raster Data

• A matrix of cells• Rows and

columns (grid)• Examples: aerial

photographs, digital photos, scanned maps

• Examples in spatial analyst…

Vector vs Raster

Raster Data

• Why do we have to use raster data?– Vector data (points, lines and polygons) are

limited to only certain spatial analyses• Point in polygon (which points are within• Line intersections

– Vector data only knows about the space it occupies

• Raster data covers the entire region• Provides a more powerful format for

advanced spatial and statistical analysis

The grid data structure

• Grid size is defined by extent, spacing and no data value information– Number of rows, number of column– Cell sizes (X and Y) – Top, left , bottom and right coordinates

• Grid values – Real (floating decimal point)– Integer (may have associated attribute

table)

Definition of a Grid

Numberof

rows

Number of Columns(X,Y)

Cell size

NODATA cell

Value attribute table for categorical (integer) grid

data

So now that I know what a raster is… what can I do with

it?• derive new information from your

existing data, • analyze spatial relationships, • build spatial models, and • perform complex raster operations.

Applications of spatial analysis

• Find suitable locations• Model and visualize crime

patterns • Analyze transportation

corridors• Perform land use analysis • Conduct risk assessments• Predict fire risk• Determine erosion potential • Determine pollution levels• Perform crop yield analysis

How to find “suitable” locations

• Step 1: State the Problem– Find the most suitable location for a new long-term care

facility in Long Beach

• Step 2: Identify the Parameters and Weight– Supply: needs to be far from existing facilities (weighted

by number of beds in the facilities) (25%)

– Demand: number of persons over 65 (50%)

– Access: close to major streets (25%)

• Step 3: Prepare Your Input Datasets– Long Beach Facilities (point)– Census Tracts – Age>65 (polygon)– Major Streets (line)

• Step 4: Perform the Analysis

ArcGIS Workflow• ArcCatalog:

– Make sure all your layers are in the same projection (eg: UTM Zone 11N)

• ArcMap: 1. Load all your layers, double check that you are on

the right projection and units (eg: miles)2. Turn on Spatial Analyst Toolbar3. Set the Environment (very important, ensures that

raster layers have the same cell size!)4. Load your indicator layers5. “Rasterize” your layers (Ex: Kernel Density, Feature

to Raster, Euclidean Distance)6. Reclassify7. Apply weights8. Generate final raster

Step 1Ensure that each layer in your project has the SAME projection

Step 2Check the map units*Even if you change the “display” units, spatial analysis will be conducted using the “map” units

Step 3Access ArcToolbox Environments

Or…

From the file menu:Geoprocessing, Environments

Right click

Step 4Set the environment1. Processing Extent

Usually set this to the extent of your project, or the largest layer

2. Raster AnalysisCell size and Mask

Step 5Diagram your work flow

Best site for new facility

Kernel Density

on Number of Beds

Feature to Raster

on Age>65

Euclidean Distance

Long Beach Facilities

Long Beach Census Tracts

Long Beach Major Roads

Far from existing facilities

Close to areas with

high numbers of

senior citizens

Close to major streets

25%

50%

25%

Step 6Do the analysis

Example: Kernel Density

Spatial Analysis Tools > Density > Kernel Density

Example: Euclidean Distance

Spatial Analysis Tools > Distance > Euclidean Distance

Example: Feature to Raster

Conversion Tools > To Raster > Feature to Raster

Long Beach

Facilities

Long Beach Census Tracts

Long Beach Major Roads

Kernel Density

on Number of Beds

Feature to Raster

on Age>65

Euclidean Distance

Reclassify:3 most

desirable1 = least desirable

Reclassify:3 most

desirable1 = least desirable

Reclassify:3 most

desirable1 = least desirable

3 3

1 3

3

2

1 1 2

1 1

1 2

3

3

2 2 3

2 1

2 1

3

1

2 2 1

Spatial Analysis Tools > Reclass > Reclassify

3 3

1 3

3

2

1 1 2

1 1

1 2

3

3

2 2 3

2 1

2 1

3

1

2 2 1

Long Beach

Facilities

Long Beach Census Tracts

Long Beach Major Roads

25%

50%

25%

.75

.75

.25

.75

.75

.5

.25

.25

.5

.5 .5

.5 1

1.5

1.5

1 11.5

.5.25

.5.25

.75

.25

.5 .5.25

1.75 1.5

1.25

2

3

2.25

1.75

1.75

2.25

Spatial Analysis Tools > Map Algebra > Raster Calculator