GEOL 404504 Advanced GIS

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GEOL 404/504 Advanced GIS

• Sudhanshu Sekhar Panda, PhD
• Lecturer/GeoSTAC Coordinator
• GIS Training and Research Center
• Idaho State University
• Spring 2006

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Lecture 8Advanced Spatial Analysis
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Definition of Spatial Analysis

• Spatial analysis could be described as techniques
  to analyze geographic data to solve real world
  problems related to spatial locations and their
  dimensions
• Spatial analysis is a way of analysing data that
  explicitly incorporates information about
  location as well about attribute. This term may
  be used almost interchangeably with geographical
  data analysis (Extracted from hds.essex.ac.uk/g2g
  p/gis/sect101.asp)
• Refer to your previous lecture on Principles of
  GIS Class (http//giscenter.isu.edu/training/
  Basic spatial analysis (Week11) )

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Definition of Spatial Analysis

• Spatial analyses are applied to solve problems
  related to geographic decisions
• Identify high crime area
• Identifying and measuring urban sprawl
• Study of population growth dynamics in urban and
  rural area
• Generate a list of roads that contribute towards
  NPS pollution
• Selection of a best location for a new business
• Determine the spread of nucleotides in
  underground aquifer
• Extent of sage brush infestation in Idaho
• Spread of a disease in western states of US
• Wolf habitat suitability map generation
• Contribution of watersheds for stream water
  quality
• Etc

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Why Spatial Analysis?

• Geographic attributes are good at representing
  geographic objects with distinct shapes
• But less good with geographic objects that are
  distributed continuously across a surface

• Temperature
• Rainfall
• Soil properties
• Elevation
• Sun exposure
• Water and air pollution level

• Distance to the nearest hospital
• Crime concentrations
• Land cover
• Noise levels
• Soil erosion rate
• Etc

• These continuous data do not have a definite
  shape
• But can be represented or measured for a
  particular location or for different locations

ESRI, 2006
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Spatial Analysis Operation

• Spatial analysis deals with function and
  operation interchangeably.
• Spatial operations could be applied sequentially
• An output could serve as input for the next
  operation
• You must know which spatial operations you need
  to apply in which sequence to have your intended
  result

Bolstad, 2005
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Spatial Analysis Operation(Cont.)

• You can use many spatial operations to one input
  to have many outputs
• You can use a single spatial operation to many
  inputs to have one output
• Can use one operation to have one output from one
  input

Bolstad, 2005
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Spatial Analysis Functions

• Buffer
• Clip or window
• Overlay
• Intersect
• Union
• Identity
• Near or Distance (proximity)
• Dissolve

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Buffer

• A buffer operation is one of the most common
  spatial analysis tools. 
• A buffer is a map feature that represents a
  uniform distance around a feature. 
• When creating a buffer, the user selects the
  feature to buffer from, as well as the distance
  to be buffered.
• The buffer operation creates a new polygon data
  set, where a specified distance is drawn around
  specific features within a layer. 
• The distances can either be constant or can vary
  depending upon attribute values. 
• When features are close together, their buffers
  may overlap. The user can choose to preserve the
  overlaps or remove them.

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Buffer tool in Arc-Tool Box

• Analysis Tools
• select Proximity
• Buffer tool

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Clip or Window
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Overlay

• A common spatial analysis tool
• Overlays allow the user to identify areas where
  features in two layers overlap. 
• A new data set is often created from these
  overlaps. 
• In a Union Overlay, all features are included in
  the new data set but the features that overlap
  represent a new feature. 
• In an Intersect Overlay, only the areas that
  overlap are contained in the new data set.

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Overlay Example

• Analysis Tools
• select Overlay
• Intersection tool

• Analysis Tools
• select Overlay
• Union tool

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Overlay Example
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Identity

• Arc/Info
• Point coverage
• Polygon coverage
• What type of polygon is found at this point
  location?
• Boolean or nominal values (overlay polygon
  coverage and point file)
• Polygon coverages for the layers should be
  overlaid on a point coverage of the grid cell
  centroids using an overlay process using Identity
  command in ArcGIS, to assign the environmental or
  planning geography to each cell in grid. 
• Generally, planning and political layers are
  dealt with in this fashion.
• Fractional/Percentage values (overlay polygon
  coverage and grid cell coverage)
• Polygon coverages for the layers should be
  overlaid on a grid cell coverage using an overlay
  process using Identity command in ArcGIS, to
  determine the areas of environmental or planning
  geography in each cell in the grid. 
• These areas can then be summed by grid cell and
  be used to calculate the percentage of grid cell
  covered by a particular geography. 
• Generally, environmental layers are dealt with in
  this fashion.

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Near or Distance
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Distance Operation
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Dissolve

• Merge adjacent polygons with same attributes.
• DISSOLVE ltINgt ltOUTgt ltDISSOLVE ITEMgt

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Other Spatial Analyses

• Surface analysis
• Interpolation
• 3-D analysis
• Map algebra
• Cell statistics

ESRI, 2006
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Surface Analysis

• Surface analysis could be both topographic and
  non-topographic
• Non-topographic Surface analysis
• Topographic surface analysis

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Topographic Surface Analysis

• Surface analysis can generate
• Contour maps
• Slope maps
• Aspect maps
• Hillshade maps
• Viewshed maps

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Surface Interpolation

• Surface interpolation is a part of geostatistics
• Interpolation is the process of estimating
  unknown values that fall between known values
• Spatial interpolation calculates an unknown value
  from a set of sample points with known values
  that are distributed across an area

ESRI, 2006
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Spatial Interpolation Methods

• Four common interpolation methods used in ArcGIS
• Inverse Distance Weighted (IDW)
• Spline
• Natural Neighbor
• Kriging

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Spatial Interpolation Methods (cont.)
Learn more on spatial interpolation methods in
Geostatistical Spatial Data Analysis (GEOL
606) class
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3-D Analysis

• ArcScene
• ArcGlobe

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3-D Analysis (Other Examples)
ESRI, 2006
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Map Algebra

• Map Algebra is an informal language for
  manipulating representations of continuous and
  discrete spatial variables defined over a common
  domain
• In general, it does not introduce any new
  capabilities within GIS analysis
• Vector A Vector B map algebra application
  could be performed using Union command
• But it provides systematic and precise way to
  manage processes performed on GIS datasets
• If you can think processing GIS data in a
  mathematical manner, map algebra can help

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Map Algebra Operators
ESRI, 2006
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Map Algebra Application
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Map Algebra Usage

• Use expression
• Multi-output map algebra
• Single output map algebra

ESRI, 2006
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Cell Statistics

• Statistics is needed to describe your data
  (raster/vector)
• Traditionally, statistics are used on a random
  but representative subset and the results are
  extrapolated to the larger group
• The subset of the population is called sample
• Descriptive statistics used mostly used with GIS
  data in stead of inferential statistics
• Inferential statistics does not include tools for
  representing geographic data

ESRI, 2006
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What Cell Statistics Do for You?

• You can
• Create new raster datasets using the Cell
  Statistics function
• Create new raster datasets using the Neighborhood
  Statistics function
• Analyze spatial data using the Zonal Statistics
  function
• Generalize spatial data
• Clean up NoData speckling in a raster dataset

ESRI, 2006
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Different Cell Statistics

• You can use the following statistical methods for
  cell, neighborhood, and zonal functions
• Majority determines the value that occurs most
  often.
• Minority determines the value that occurs least
  often.
• Maximum determines the highest value.
• Minimum determines the lowest value.
• Range computes the difference between the
  highest and lowest values.
• Mean computes the total of the values divided by
  the number of observations.
• Median computes the central value, where there
  are an equal number of values above and below it.
  
• Standard Deviation computes the spread or
  dispersion of values from the mean.
• Sum computes a total value by adding all of the
  values.
• Variety determines the number of different
  values.

ESRI, 2006
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With Spatial Analysis Tools Use What You Can Do?

• Find suitable locations.
• Find the best path between locations.
• Perform integrated raster/vector analysis.
• Perform distance and cost-of-travel analyses.
• Perform statistical analysis based on the local
  environment, small neighborhoods, or
  predetermined zones.
• Generate new data using simple image processing
  tools.
• Interpolate data values for a study area based on
  samples.
• Clean up a variety of data for further analysis
  or display.