Post on 11-Feb-2018
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Sonoma County: Examples of GIS Analysis in Local Government
Decision Support
Tim Pudoff, GIS Manager and Adjunct Instructor,
County of Sonoma Santa Rosa Junior College
BAAMA User Meeting – January 19, 2010
Sonoma County• North of Marin
County• ~1580 square miles• ~465,000 people• 9 incorporated cities• http://www.sonoma-
county.org• County GIS capability
– ISD / GIS Central– Department Staff
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Overview
• What is “spatial analysis”?• Why should local government investigate and
incorporate elements of spatial analysis into its workflows?
• How complicated is it to incorporate spatial analysis into government work flows?
• What steps are required for collecting and organizing data for spatial analysis?
• Examples of using spatial analysis in Sonoma County interspersed throughout presentation
What is Spatial Analysis?
• In practical terms, spatial analysis answers the following:– What are the patterns of a distribution (clustered,
dispersed, or random)?
– What is the relationship between two mapped phenomena that appear to be correlated?
– What If …? Can I predict the resulting pattern using certain inputs to a model?
– Beware of interpreting “causal effect” as opposed to “spatial interaction”
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Why should local government investigate and incorporate elements of spatial analysis into its workflows?
• We are mandated to protect public health and safety, enhance and protect the environment, and local economy
• We have a good idea the local conditions
• Our expert knowledge enables us to compare existing with past and potentially future scenarios
• If we don’t do it, who will?
Overview
• You should be guided by a philosophy and a process
– Data driven decision-making
– Geographic inquiry process
– Starts with asking questions
• Analysis is an approach to decision support, not an end result
Source: ESRI Virtual Campus,
Learning ArcGIS 9
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Classic GIS Analysis
• Overlay analysis or proximity analysis– i.e., what do I overlap or
what is nearby?
– Am I in the flood plain?
– How much area is this type of category?
– Etc., etc.
• Complements spatial analysis
Source: Sonoma County PRMD ActiveMap
A variant of the original map drawn by Dr. John Snow (1813-1858), a British physician who is one of the founders of medical epidemiology, showing cases of cholera in the London epidemics of 1854, clustered around the locations of water pumps. (Source: http://en.wikipedia.org/wiki/File:Snow-cholera-map.jpg)
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Sample questions for spatial analysis
• Does the distribution of cases of a disease (e.g., pertusis) form a pattern in space?
• Where do we offer immunization to support those of modest incomes?
• Can we reach those in need?
• Starts with mapping what you know
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Questions for spatial analysis
• Does the spread of insect infestation form a pattern in space and time?
• Do I have adequate data describing the distribution?
• If I have to collect new data, how do we gather samples to ensure that we are able to track change through time?
Creating a Grid for Spatial Sampling
Spatial autocorrelation is scale dependent. What size sampling grid is appropriate?
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Questions for spatial analysis
• What is the distribution of clients using our health services?
• Are they correlated to level of income?
• Are low or modest income clients within walking distance of public transportation?
• Where is the best place to locate the clinic?
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Types of Spatial Analysis
• Spatial Statistics
– Spatial Autocorrelation
– Spatial Interpolation
– Spatial Regression
– Spatial Interaction (“gravity models”)
• Geovisualization (Gvis)
– Human-oriented pattern recognition
• Geographic knowledge discovery (GKD)
– Data mining, selection, scrubbing and interpretation
Spatial Autocorrelation
• A fundamental concept in geography is that “nearby entities often share more similarities than entities which are far apart”.
• 'Tobler's first law of geography' and may be summarized as "everything is related to everything else, but near things are more related than distant things“
• The opposite of spatial dependency is “complete spatial randomness”.
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Spatial Autocorrelation
• Characteristics at proximal locations appear to be correlated, either positively or negatively.
• We can test for the degree of “spatial autocorrelation” in data using a statistical tool such as “Moran’s I (global)”
Source: ESRI, ArcGIS 10 Online Help
Spatial Interpolation• Estimation of unknown values on a surface
from a sample of known values
• The principle underlying spatial interpolation is Tobler's Law (of spatial autocorrelation)
Source: ESRI, Turning Data Into Information
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Sample Interpolated Surface
Geo-visualization example
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How complicated is it to incorporate spatial analysis into government work
flows?
• Learning spatial statistics requires a minimum investment of a semester of school in an intermediate or advanced GIS class that covers the concepts
• Can take much longer to “master”, and may require consultation with subject matter experts (e.g., epidemiologists, statisticians, etc.)
• A good starting place – Carefully collect and examine existing database– Plot data for visualization and develop spatial questions– Take a class at your local community or state college or
pursue online education
What steps are required for collecting and organizing data for spatial
analysis?
1. Identify a resource (you?) to perform the analysis
2. Ask the initial spatial question (where) related to the subject
3. Acquire the data
• Starting with GIS or non-spatial data?
• Client databases can usually be “geocoded” to create a point distribution
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Finding the Data
• Likely, someone is already maintaining it …
– In Written Reports (!?)
– Spreadsheets
– Standard Relational Databases (e.g., Access, SQL Server, etc.)
– Complex Systems (CAD/RMS, property, etc.)
– Enterprise GIS System (!)
– Internet (web service, ODE, etc.)
Making Data Spatial - The Art and Soul of Geocoding
Microsoft Excel Table
4. Explore the Data 5. Analyze the Data
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What steps are required for organizing data for spatial analysis?
5. Analysis can take many forms• Distribution can be converted to a surface using
spatial interpolation techniques
• Alternately, distribution can be analyzed for clustering or dispersion
• Some data, such as service areas, can be generated from GIS network data sets (i.e., streets)
• These patterns can then be plotted and visually analyzed to develop spatial questions
• Spatial questions lead you to additional tools and sampling methods, and analysis
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Types of Spatial Analysis Tools
• Sample “Tools” from ESRI ArcGISDesktop– 3D and Raster Analysis: Line of
Sight, Interpolation (Kriging), Slope and Aspect, Map Algebra, Density mapping
– Vector Analysis: Clip, Intersect, Buffer
– Geocoding*: Addresses, XY event– Linear Referencing– Network Analysis: Service area and
vehicle routing– Spatial Statistics: Pattern analysis,
mapping clusters and distributions
Simple client distribution sample
Which citizens with land lines are within the call zones?
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More complex client surface analysis
• What is the current client distribution (surface and mean center)?
• How close are they to the existing clinic location?
• What is the best location for the new clinic based on finding the shortest distance traveled for a majority of citizens while remaining accessible to public transportation?
• What are potentially underserved areas based on household income and other socio-economic indicators?
Resources for this Presentation
• Data and Maps used Courtesy of the County of Sonoma Departments of Health Services, Human Services, and Fire and Emergency Services, Agricultural Commissioner, http://www.sonoma-county.org
• Spatial Analysis, Wikipeida, http://en.wikipedia.org/wiki/Spatial_analysis
• Spatial Analysis and GIS: A Primer, Gilberto Câmara, et al., www.dpi.inpe.br/gilberto/.../spatial_analysis/spatial_analysis_primer.pdf
• The ESRI Guide to GIS Analysis, Vol. 2, by Andy Mitchell and ESRI, 2005.
• Turning Data into Information Using ArcGIS 9, by ESRI and Paul A. Longley, Ph.D., Michael F. Goodchild, Ph.D., David J. Maguire, Ph.D., and David W. Rhind, Ph.D., http://training.esri.com/Courses/DataInfo9/index.cfm?c=145.
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Questions
• Tim Pudoff, GIS Manager
• County of Sonoma
• Information Systems Department
• Santa Rosa CA 95403
• tpudoff@sonoma-county.org
• 707-565-1941