NTENBeyond Dots On Maps: Geographic Data Analysis for Non-Profits
Upcoming SlideShare
Loading in...5
×
 

NTENBeyond Dots On Maps: Geographic Data Analysis for Non-Profits

on

  • 590 views

Presentation on geographic data analysis for non-profit organizations at the National Non-profit Technology Conference in Atlanta, GA. Contact me at cheetham@azavea.com for a PDF resource guide.

Presentation on geographic data analysis for non-profit organizations at the National Non-profit Technology Conference in Atlanta, GA. Contact me at cheetham@azavea.com for a PDF resource guide.

Statistics

Views

Total Views
590
Views on SlideShare
590
Embed Views
0

Actions

Likes
0
Downloads
4
Comments
0

0 Embeds 0

No embeds

Accessibility

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • I wouldn’t normally encourage people to skip my presentation, but…
  • Registration problems -people who had voted in the same place for years, not changed anything, yet not on the rolls -people who had registered before the deadline but weren’t in the book -people who were listed with a party other than the one they registered for
  • We geocoded these records giving each a location in south east PA.
  • We then joined these geocoded records with census tracts to produce thematic maps showing the distribution of supporters.
  • And we created density maps of Wilma supporters. This was in particular very helpful to enable the Wilma to see the differences in dense urban areas like center city philadelphia.
  • Analysis: Maps Map Output: This should be a Temple slide with red -> orange color ramp
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • Table view at top 2 screensshots below with Trend Chart in one and Index Map in 2nd
  • We selected a variety of factors that contribute to sustainability, ranging from location in a state or federal tax incentive zone to environmental amenities like tree canopy to transit considerations like access to bus and regional rail lines. Retail businesses targeting markets may be interested in demographic factors like age and per capita income and proxies for environmental engagement like recycling participation.
  • Now imagine if you could input all of these factors, assign weights to each one of them and generate a map with the hot spots lit up. Now that would help me find the best neighborhood... or site a business... or, depending on the input factors, prioritize your marketing campaign. So that’s what we decided to do. But we weren’t the first.
  • So, these days people do this kind of work using desktop GIS systems. You are looking at the ArcMap application from ESRI
  • scenarios
  • Heat map
  • Export to KML
  • A few years ago we had developed the Cicero elected official lookup. To do this, we amassed a lots and lots of shapefiles of district boundaries. We noticed that Philadelphia had some pretty astonishingly contorted boundaries. We were wondering, how bade were they really? We happened to have all this spatial data handy, so we figured we could put our GIS & spatial analysis skills to find out.
  • Mention that all of the ideas we’ll introduce can be implemented
  • Mention that all of the ideas we’ll introduce can be implemented
  • Mention that all of the ideas we’ll introduce can be implemented
  • Mention that all of the ideas we’ll introduce can be implemented
  • Mention that all of the ideas we’ll introduce can be implemented

NTENBeyond Dots On Maps: Geographic Data Analysis for Non-Profits NTENBeyond Dots On Maps: Geographic Data Analysis for Non-Profits Presentation Transcript

  • Beyond Dots on a Map: Geographic Data Analysis for Non-Profits Robert Cheetham 9 April 2010
  • About Azavea
    • Founded in 2000
    • Web & Mobile GIS apps
    • Spatial Analysis
    • R&D
    • B Corporation
    • Economic Development
    • Municipal Services
    • Culture
    • Elections & Politics
    • Public Health
    • Land Conservation
    • Public Safety
    • Human Services
    Clients and Industries Carnegie Mellon
  • What will I talk about?
    • Applying geography to help non-profits
    • Case Studies
    • Advanced analysis
    • Creative applications of geography
    • Analysis tools
    • Data Resources
    • What are your experiences with GIS and Mapping?
  • The Dots
  • The Dots
  • The Dots
  • Case Study 1: Mural Arts Program
  • Arts: Geographic Collection Management
  • Arts: Geographic Collection Management
  • Arts: Geographic Collection Management
  • Arts: Geographic Collection Management
  • Arts: Geographic Collection Management
  • Arts: Geographic Collection Management
  • Case Study 2: United Way - CONNECT 2-1-1
  • Geographic I&R – CONNECT 2-1-1
  • Geographic I&R – CONNECT 2-1-1
  • Geographic I&R – CONNECT 2-1-1
  • Geographic I&R – CONNECT 2-1-1
  • Geographic I&R – CONNECT 2-1-1
  • Geographic I&R – CONNECT 2-1-1
  • Case Study 3
  • © Photo used with permission from BlondSage , via Flickr.com
  • Election Day Monitoring
  • Election Incidents
  • Election Incident Monitoring
  • Election Incidents
  •  
  •  
  •  
  •  
  • Case Study 4: Wilma Theater – Finding More Patrons
  • Extract databases of existing supporters: Subscribers, donors, and single ticket buyers Geocoding databases of existing supporters, determine analysis extent
  • Extract databases of existing supporters: Subscribers, donors, and single ticket buyers Geocoding databases of existing supporters, determine analysis extent Create census tract level aggregations of supporters in Metropolitan Philadelphia
  • Extract databases of existing supporters: Subscribers, donors, and single ticket buyers Geocoding databases of existing supporters, determine analysis extent Create density maps of subscribers, donors, and single ticket buyers Create census tract level aggregations of supporters in Metropolitan Philadelphia
  •  
  •  
  •  
  •  
  •  
  • 1 Location of Wilma supporters in Metro Philadelphia
  • 1 2 Location of Wilma supporters in Metro Philadelphia Census tracts with demographic data on small areas + People Per Square Mile Median Age % College Educated or Higher Average Household Size Average Family Size Number of Gay/ Lesbian Couples Household Income Per Capita Income
  • 1 2 3 2 Location of Wilma supporters in Metro Philadelphia Each supporter is ‘stamped’ with demographic qualities based on its census tract Census tracts with demographic data on small areas + = People Per Square Mile Median Age % College Educated or Higher Average Household Size Average Family Size Number of Gay/ Lesbian Couples Household Income Per Capita Income
  • 1 2 3 2 Location of Wilma supporters in Metro Philadelphia Each supporter is ‘stamped’ with demographic qualities based on its census tract Census tracts with demographic data on small areas + = People Per Square Mile Median Age % College Educated or Higher Average Household Size Average Family Size Number of Gay/ Lesbian Couples Household Income Per Capita Income
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 1 2 3 2 Location of Wilma supporters in Metro Philadelphia Each supporter is ‘stamped’ with demographic qualities based on its census tract Census tracts with demographic data on small areas + = People Per Square Mile Median Age % College Educated or Higher Average Household Size Average Family Size Number of Gay/ Lesbian Couples Household Income Per Capita Income
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 6,698 People Per Square Mile 37.01 Median Age 18% % College Educated or Higher 2.59 Average Household Size 3.14 Average Family Size 9 Number of Gay/ Lesbian Couples $51,045 Household Income $23,923 Per Capita Income Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 6,698 People Per Square Mile 37.01 Median Age 18% % College Educated or Higher 2.59 Average Household Size 3.14 Average Family Size 9 Number of Gay/ Lesbian Couples $51,045 Household Income $23,923 Per Capita Income Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 12,521 6,698 People Per Square Mile 38.97 37.01 Median Age 38% 18% % College Educated or Higher 2.26 2.59 Average Household Size 2.89 3.14 Average Family Size 27 9 Number of Gay/ Lesbian Couples $62,518 $51,045 Household Income $37,009 $23,923 Per Capita Income Wilma Subscribers Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 2.27 38.81 12,078 2.89 38% 27 $64,124 $37,961 Wilma Donors 12,521 6,698 People Per Square Mile 38.97 37.01 Median Age 38% 18% % College Educated or Higher 2.26 2.59 Average Household Size 2.89 3.14 Average Family Size 27 9 Number of Gay/ Lesbian Couples $62,518 $51,045 Household Income $37,009 $23,923 Per Capita Income Wilma Subscribers Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 2.27 38.81 12,078 2.89 38% 27 $64,124 $37,961 Wilma Donors 2.21 37.8 14,792 2.87 35.8% 31 $54,475 $34,326 Wilma Single Ticket Buyers 12,521 6,698 People Per Square Mile 38.97 37.01 Median Age 38% 18% % College Educated or Higher 2.26 2.59 Average Household Size 2.89 3.14 Average Family Size 27 9 Number of Gay/ Lesbian Couples $62,518 $51,045 Household Income $37,009 $23,923 Per Capita Income Wilma Subscribers Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 2.27 38.81 12,078 2.89 38% 27 $64,124 $37,961 Wilma Donors 2.21 37.8 14,792 2.87 35.8% 31 $54,475 $34,326 Wilma Single Ticket Buyers 12,521 6,698 People Per Square Mile 38.97 37.01 Median Age 38% 18% % College Educated or Higher 2.26 2.59 Average Household Size 2.89 3.14 Average Family Size 27 9 Number of Gay/ Lesbian Couples $62,518 $51,045 Household Income $37,009 $23,923 Per Capita Income Wilma Subscribers Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 12,078 38% $64,124 Wilma Donors 14,792 35.8% $54,475 Wilma Single Ticket Buyers 12,521 6,698 People Per Square Mile 38% 18% % College Educated or Higher $62,518 $51,045 Household Income Wilma Subscribers Philadelphia Metro
  • Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 12,078 38% $64,124 Wilma Donors 14,792 35.8% $54,475 Wilma Single Ticket Buyers 12,521 6,698 People Per Sq Mile 38% 18% % College Educated $62,518 $51,045 Household Income Wilma Subscribers Philadelphia Metro
  • > $55K > 35% > 2,000 Target Demographic Summarize these values to develop the ‘average’ Wilma Patron’s neighborhood 12,078 38% $64,124 Wilma Donors 14,792 35.8% $54,475 Wilma Single Ticket Buyers 12,521 6,698 People Per Sq Mile 38% 18% % College Educated $62,518 $51,045 Household Income Wilma Subscribers Philadelphia Metro
  • + Density of Current Supporters Philadelphia Most Desired Areas Using this information to find untapped markets in the Philadelphia Metro Area
  • + = Density of Current Supporters Untapped Communities Philadelphia Most Desired Areas Using this information to find untapped markets in the Philadelphia Metro Area
  •  
  •  
  • Case Study 5: PhillyHistory.org
  •  
  • Buying Stuff
  • Buying Stuff
  • Buying Stuff
  • Case Study 6: Applying for Grants
  • Community Indicators
  • Community Indicators
  • DOJ Grant Applications
  • DOJ Grant Applications
  • DOJ Grant Applications
  • DOJ Grant Applications
  • Community Statistical Systems
  • Community Statistical Systems
  • Community Statistical Systems
  • Case Study 7: Sustainable Business Network
    • Tax Incentives
    • Commercial Corridor Health
    • Public Transit
    • Car Share
    • Open Space
    • Farmers’ Markets
    • Street Network Density
    • Recycling Participation
    • Walkability
    Sustainability Factors
  • Public Transit  Grocery Store  Restaurants  Library  Park  Walk to Work  Fencing  ZipCar  View of Waterfront  Find the best places to live, work and sell
  • x 5 x 2 x 3 x 1 + + + = Generate Output Heat Map
  • Desktop GIS
  • Sustainable Business Network
  •  
  •  
  •  
  • Reports
  • Reports
  •  
  •  
  •  
  • Walkability: Walkshed.org
  • Walkability: Walkshed.org
  • + + + + + + + + =
  •  
  • Land Conservation
  • Off the Beaten Path – Creative Applications of Geography
  • Reform Ballot
  •  
  •  
  •  
  •  
  •  
  •  
  •  
  • MAPLight.org – Campaign Contribution Analysis
  •  
  •  
  • Early Warning Systems
  • Early Warning Systems
  •  
  • Tools and Data
  • Free or Low Cost Geocoding
    • ESRI ArcGIS Online (ArcGIS.com)
    • BatchGeo.com
    • Geocoder.us
    • Geonames.com
    • GoogleMaps API
    • Bing Maps API
    • Cloudmade
  • Free or Low Cost Base Maps
    • ESRI ArcGIS Online (ArcGIS.com)
    • GoogleMaps API
    • Bing Maps API
    • Yahoo Maps API
    • OpenStreetMap.org
    • Cloudmade.com
  • Free or Low Cost GIS Data Viewers (little or no analysis)
    • ESRI ArcGIS Explorer
    • Google Earth
    • Google Earth Pro (free to non-profits)
    • Quantum GIS (open source)
    • uDig (open source)
  • Low Cost Desktop GIS Analysis
    • ESRI ArcGIS Desktop
    • GeoDA (free, advanced statistical analysis)
    • GRASS
    • Manifold GIS
  • Online Data and Mapping Systems
    • ESRI ArcGIS Online (ArcGIS.com)
    • GeoCommons.com
    • PolicyMap.com
  • Spatial Databases and Data Feed Formats
    • Shapefiles: free, simple features
    • Personal GeoDB: free, Windows only, complex features
    • File GeoDB: free, complex features
    • ESRI Enterprise GeoDB: licensed, works with RDBMS, complex features
    • PostGIS: open source, PostgreSQL, moderately complex features
    • Oracle Spatial: licensed, Oracle only, moderately complex features
    • MS SQL Server Spatial: licensed, SQL Server only, simple features
    • SQLite Spatial: open source, simple features, embedded db
    • MySQL Spatial: open source, simple features
    • KML: free, cross-platform, mostly for display only)
    • GeoRSS: free, cross-platform, embeds geography in RSS)
    Most common cross-platform interchange formats
  • Web Map Servers
    • ESRI ArcGIS Server (commercial)
    • GeoServer (open source)
    • MapGuide (open source)
    • Mapnik (open source – high quality cartography)
    • UMN MapServer (open source)
  • U.S. Data Resources
    • American FactFinder
    • Data.gov – http://www.Data.gov/
    • ESRI ArcGIS Online
    • ESRI DVD’s (free with software)
    • GeoCommons
    • GeoData.gov – http://www.GeoData.gov/
    • Local Government
    • MIT Libraries - State Data Clearinghouses
    • USGS
  • International Data Resources
    • Data.gov.uk
    • ESRI ArcGIS Online
    • ESRI DVD’s (free with software)
    • GeoCommons Finder
    • OpenStreetMap.org
    • NASA JPL
    • Penn State Libraries (Digital Chart of the World)
    • U-Chicago Libraries
    • USGS Seamless
  • Many Thanks! © Photo used with permission from Alphafish , via Flickr.com
  • Evaluation Code: 204 How Was this Session? Call In Text Online Call 404.939.4909 Enter Code 204 Text 204 to 69866 Visit nten.org/ntc-eval Enter Code 204 Session feedback powered by: Tell Us and You Could Win a Free 2011 NTC Registration!
  • Beyond Dots on a Map Geographic Data Analysis for Non-Profits Robert Cheetham [email_address] 9 April 2010