Sonoma County: Examples of GIS Analysis in Local ...3dmap.me/baama_org/Tim_Pudoff_Sonoma_Co_GIS... · 1/20/2011 1 Sonoma County: Examples of GIS Analysis in Local Government Decision

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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

• [email protected]

• 707-565-1941