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September 18-19, 2006 – Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development Using Geographic Information Systems (GIS) as.

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Presentation on theme: "September 18-19, 2006 – Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development Using Geographic Information Systems (GIS) as."— Presentation transcript:

1 September 18-19, 2006 – Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development Using Geographic Information Systems (GIS) as a tool for HMIS decision making Jon-Paul Oliva, M.S. GIS Consultant jon.paul.oliva@gmail.com

2 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 2 What is a GIS? Broadly, a method of organizing data using a spatial scheme

3 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 3 What is a GIS? Broadly, a method of organizing data using a spatial scheme A map (or series of maps) that can reference a database

4 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 4 What is a GIS? Broadly, a method of organizing data using a spatial scheme A map (or series of maps) that can reference a database Computer based system for storage, synthesis, analysis and reporting of large quantities of spatial data and associated information

5 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 5 Where does the GIS data come from? Three main sources of GIS data:

6 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 6 Where does the GIS data come from? Three main sources of GIS data:  Digitizing of paper based maps

7 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 7 Where does the GIS data come from? Three main sources of GIS data:  Digitizing of paper based maps  Earth Observation (Satellites & Survey)

8 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 8 Where does the GIS data come from? Three main sources of GIS data:  Digitizing of paper based maps  Earth Observation (Satellites & Survey)  Global Positioning Systems (GPS)

9 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 9 Where does the GIS data come from? Three main sources of GIS data:  Digitizing of paper based maps  Earth Observation (Satellites & Survey)  Global Positioning Systems (GPS) These sources are then linked with your (HMIS) data within a GIS

10 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 10 Data Structures Three main types of data structures:

11 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 11 Data Structures Three main types of data structures:  Vector - points, lines & polygons - Used to define addresses, roads, external boundaries

12 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 12 Data Structures Three main types of data structures:  Vector - points, lines & polygons - Used to define addresses, roads, external boundaries  Raster - Grid data, earth observation imagery - used to analyze density and detect trends in landscape level features

13 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 13 Data Structures Three main types of data structures:  Vector - points, lines & polygons - Used to define addresses, roads, external boundaries  Raster - Grid data, earth observation imagery - Grid data, earth observation imagery - used to analyze density and detect trends in landscape level features  Tabular - Data tables & database structures - Database stored attributes that provide descriptive statistics for map features

14 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 14 Data Structures Data structures containing different types of data are combined in layers in the GIS to answer questions of interest

15 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 15 Datums, Map Projections and Coordinate Systems Maps are by definition a two dimensional representation of three dimensional space, composed of three parts:  The map datum specifies the spheroid shape of the earth  The map projection dictates how the three dimensional space will be represented on a flat surface  Coordinate systems describe the particular convention for measuring distance on the map (x,y - e.g. latitude/longitude, UTM) All Map Projections introduce some distortion of geographic shape, area or distance Projection parameters are selected for accuracy in representing data at different scales and locations Take home message: When working with multiple GIS layers, each layer must use the same set of datum, projection and coordinate system parameters

16 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 16 A Geographic Coordinate System An Albers Coordinate System Datums, Map Projections and Coordinate Systems

17 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 17 What might a GIS look like? Map Link Zipcodes Database Spatial referenceData of interest Area of interest

18 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 18 Example Analysis - Mapping 2006 HMIS Data 2006 Family Data - 1st Time Homeless

19 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 19 Example Analysis - 1. Add GIS Data to Create a New Project

20 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 20 Example Analysis - 1. Add GIS Data to Create a New Project

21 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 21 Example Analysis - 2. Add Contextual Data to Provide a Reference

22 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 22 Example Analysis - 3. Classify Data Using Data Attribute Tags

23 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 23 Example Analysis - 4. Link External HMIS Data Using Zipcode

24 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 24 Example Analysis - 5. Classify Zipcode Data Using Desired HMIS Data

25 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 25 Example Analysis - 6. Add a Legend and Scale in Layout Mode

26 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 26 Some Additional Examples - Reporting National Statistics Visually

27 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 27 Some Additional Examples - Reporting National Statistics Visually

28 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 28 Some Additional Examples - Maps Can Facilitate Regional Planning

29 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 29 Some additional examples - Discovering Unclaimed HUD Geocodes

30 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 30 Some additional examples - Sorting out Independent VA Cities

31 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 31 Some Additional Examples - Decision Making for Unique Situations

32 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 32 Some Additional Examples - Decision Making for Unique Situations

33 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 33 Some Additional Examples - Analysis of Service Locations in D.C.

34 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 34 Additional Requirements Metadata - Documentation for your GIS datasets  Distribution of GIS data by Federal Agencies requires accompanying metadata that conforms to the Content Standard for Digital Geospatial Metadata (CSDGM)  CSDGM standard was developed by the Federal Geographic Data Committee (FGDC) in response to a need for standardized documentation to describe the use, limitations, integrity and technical specifications of GIS datasets

35 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 35 Resources Free GIS software:  ESRI ArcExplorer - Win XP/Mac OS X based viewer and basic feature set software. http://www.esri.com/software/arcexplorer/  GRASS GIS - Unix/Linux/OS X based full-featured software. http://www.baylor.edu/grass/  FreeGIS.org and MapCruzin.com - information and links to open-source and public license GIS software

36 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 36 Resources Free GIS data:  US Census data (2000 and some previous data) - http://www.esri.com/data/download/census2000_tigerline/  State agencies, often in partnership with non-profit organizations and higher education, maintain statewide GIS clearinghouses for GIS data, often available for download over the internet.  Local county and municipal governments usually have a GIS staff through which local and regional data may be obtained free of charge.

37 September 18-19, 2006 - Denver, Colorado Sponsored by the U.S. Department of Housing and Urban Development 37 For additional information: Tatjana Meschede: tatjana.meschede@umb.edu David Patterson: dpatter2@utk.edu Jon Paul Olivia: jon.paul.oliva@gmail.com


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