### Spatial Analysis

```Let’s pretty it up!
Big circles…
and semitransparent
Everything
else is hardly
noticeable…
but it’s there
Border
around
project area
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
– 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
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
Cell size
Number
of
rows
NODATA cell
(X,Y)
Number of Columns
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.
2.
3.
4.
5.
6.
7.
8.
right projection and units (eg: miles)
Turn on Spatial Analyst Toolbar
Set the Environment (very important, ensures that
raster layers have the same cell size!)
“Rasterize” your layers (Ex: Kernel Density, Feature to
Raster, Euclidean Distance)
Reclassify
Apply weights
Generate final raster
Step 1
Ensure that each layer in your
project has the SAME
projection
Step 2
Check the map units
*Even if you change the “display”
units, spatial analysis will be
conducted using the “map” units
Step 3
Access ArcToolbox
Environments
Or…
Geoprocessing, Environments
Right click
Step 4
Set the environment
1. Processing Extent
Usually set this to
the extent of your
project, or the
largest layer
2.
Raster Analysis
Step 5
Best site
for new
facility
Far from
existing
facilities
25%
Close to areas
with high
numbers of
senior citizens
50%
25%
Close to
major streets
Kernel
Density on
Number of
Beds
Feature to
Raster on
Age>65
Euclidean
Distance
Long Beach
Facilities
Long Beach
Census
Tracts
Long Beach
Step 6
Do 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
Kernel
Density on
Number of
Beds
Reclassify:
3 most desirable
1 = least
desirable
Feature to
Raster on
Age>65
Reclassify:
3 most desirable
1 = least
desirable
Euclidean
Distance
Reclassify:
3 most desirable
1 = least
desirable
Spatial Analysis Tools > Reclass > Reclassify
3
3
1
3
1
2
1
2
1
1
1
3
2
2
3
2
3
2
1
2
2
3
3
1
2
1
1
3
Long Beach
Facilities
3
1
3
1
2
2
.5
1
.5
.5
Spatial Analysis Tools > Map Algebra > Raster Calculator
1.5
1.5
.25
.75
.25
.5
1.25
1.5
2
1.75
.25
.25
1.75
1.75
1.5
1
.5
1
.5
.5
1
3
1
2
.25
1
1
.75
.75
.5
3
.75
.5
3
2
2
Long Beach
.25
3
2
2
.25
2
1
1
.75
2
1
1
Long Beach
Census
Tracts
3
3
2.25
2.25
```