GIS Analysis Functions

1
GIS Analysis Functions

• INLS 110-111
• GIS Digital Information
• Uses, Resources Software Tools

2
Unlocking Information

• Approximately 80 of all information held in
  databases contains some kind of geographic
  element
• GIS can help uncover the full value of this data
• Records in a database can be tied to a particular
  location on the ground
• e.g., address, building, property or road
  junction
• GIS identifies hidden trends relationships

3
GIS Maps as Discovery Tools

• One of the best ways to analyze data is to
  produce color-coded maps that reveal patterns in
  data which may otherwise be missed.
• The thematic map
• (demo-dynamic traffic congestion)
• Visual Analysis
• (demo-recognizing spatial patterns using GIS)

4
GIS Analysis Functions

• Four categories
• Retrieval/classification/measurement
• Overlay
• Neighborhood
• Connectivity

5
1. Retrieval, Classification, Measurement
Functions

• Retrieval
• Selective Search
• Classification/Reclassification
• Identifying a set of features as belonging to a
  group
• Defines patterns
• Measurement
• Distances, lengths, perimeters, areas

6
Retrieval Selective Search

• addresses selected because they fall within circle

7
2. Overlay Functions

• Arithmetic
• addition, subtraction, division, multiplication
• Logical
• find where specified conditions occur (and, or,
  gt, lt, etc.)
• Raster Vector methods differ
• Vector good for sparse data sets
• Raster grid calculations easier
• Overlay (demo addition)

8
3. Neighborhood Functions

• Basic Functions
• Average, diversity, majority, minimum/maximum,
  and total
• Parameters to define
• Target location(s)
• Specification of neighborhood
• Function to perform on neighborhood elements

9
3. Neighborhood Function (cont)

• Search Operation
• most common neighborhood operation
• Example
• count the number of customers within 2 miles of
  the grocery store

10
3. Neighborhood Functions (cont)

• Point or Line in Polygon Operation
• Vector Model
• specialized search function
• Raster Model
• polygons one data layer
• points or lines in separate data layer
• Buffers (demo - point, line, polygon)

11
3. Neighborhood Functions (cont)

• Thiessen Polygons Operation
• defines the individual area of influence around a
  point
• used to predict values at surrounding points from
  a single point observation
• can produce polygons with shapes unrelated to
  phenomenon being mapped

12
Example Neighborhood Function

• Thiessen Polygons

13
Neighborhood FunctionsImplementing

• Used for calculating the mean, standard
  deviation, sum,
• or range of values within the immediate or
  extended neighborhoods.

14
Neighborhood Functions4 x 4 Window Processing
15
Neighborhood FunctionsAnnulus Neighborhood
Processing
16
Neighborhood FunctionsCircular Neighborhood
Processing
17
Neighborhood FunctionsWedge Neighborhood
Processing
18
Neighborhood FunctionsExample
Zone theme Watersheds Value theme
Elevation Statistic type Mean Output
Mean elevation of each watershed
19
Neighborhood Functions10x10 averaging filter
on a DEM
20
4. Connectivity Functions

• Used to accumulate values over an area being
  navigated
• Parameters to define
• specification of way spatial elements are
  connected
• rules that specify allowed movement along
  interconnections
• a unit of measurement

21
4. Connectivity Functions (cont)

• Examples
• Network Analysis (Shortest Path, etc.)
• Size and Contiguity

22
Contiguity Functions
Combines adjacent units together when they share
a common attribute
23
Example Connectivity (Vector)

• Network Function Location-Allocation

24
Seek or Stream Functions
25
Spread Functions Travel Time Friction Surface
Friction Surface Data Layer
Start Point Data Layer
Cumulative Travel Time Data Layer
26
Spread Functions Travel Time Creating
Friction Surface
27
Spread Functions Travel Time Map
28
Spread Function Calculation of Distance
29
Spread Function Equidistant Travel Zones from
Target (A)
30
Spread Function Travel Zones-Absolute Partial
Barriers
31
4. Connectivity Functions (cont).

• Visibility Analysis Operations
• identification of areas of terrain that can be
  seen from a particular point on the surface
• Viewshed Operation
• uses digital elevation model data (DEMs) or.....
• digital terrain model data (DTMs) or......
• triangulated irregular network data (TINs)

32
Connectivity Function ExampleViewshed Analysis
Image Source Chrisman, Nicholas.(2002). 2nd Ed.
Exploring Geographic Information Systems. p 198.
fig. 8-14.
33
Intervisibility
34
Emergency Services

• Real time tracking, route-finding, best to respond

35
Flood Risk

• 3D height data changing water levels-danger areas

36

• Selecting Attributes (demo restaurant finder)
• Geocoding (demo)

37
Retail Site Selection

• Existing stores, 15 min. drive time, demograhics

38
Environmental Impact Analysis

• 3D landscape model impact on natural beauty

39
Airport Noise Pollution

• noise complaints mapped by address location

40

• Surface functions
• density, contour, interpolation functions
• aspect, slope, hillshade, etc.
• watershed analysis and modeling (flow direction,
  flow accumulation, flow length, watershed
  delineation, stream ordering)
• visibility modeling/mapping
• determine the area that can be "seen" from the
  target location

41
Analysis Summation

• GIS does not always provide exact answers to
  problems, but by identifying trends based on
  geography, GIS can reveal patterns that can help
  us make informed decisions.
• A GIS can improve decision-making it cannot make
  decisions for us.