COMMUTE Atlanta A Comparison of Geocoding Methodologies for Transportation Planning Applications Jennifer Indech Nelson Dr. Randall Guensler Dr. Hainan Li Georgia Institute of Technology May 9 th, 2007

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 2 Agenda Purpose… Background Process – Acquisition of data – QAQC – Final data set Analysis – Positional Accuracy – Polygon Assignment Discussion …Assess the accuracy of various geocoding methods to provide insight on field data collection, calibration of travel demand model inputs, and automation of travel behavior analysis

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 3 Geocoding and How It Is Used in Transportation Planning “Geocoding” - Generation of coordinates within a spatial geographic framework, where single points serve as proxies for places Used to: – Prepare TAZ data from travel diary studies for Travel Demand Model development – Better represent spatial travel patterns – Verify 4-step model components – Provide primary input to next generation behavior- based micro-simulation Travel Demand Models

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 4 Methods of Obtaining Geocoded Coordinate Data GPS field surveys (active) Aerial image processing Address matching Road network address interpolation GPS tracking (passive) Increased automation

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 5 Geocoding: Address Matching Vs. Interpolation Assign coordinates 1:1 - Check address existence / integrity from list inc. other attributes Estimate position from spatial reference (network link) Address Interpolation Address Matching Linear Address interpolation

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 6 GPS and GIS Data Acquisition in Transportation – Commute Atlanta Commute Atlanta study – GPS-instrumented vehicle tracking – 3+ years, second-by-second – 487 vehicles, 268 households – 1.8 million trips GT Server Cellular Network GPS Satellite In-vehicle Event Data Recorder Profile Data

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 7 Data for Comparative Analysis Two days of parallel data in March 2004 from 137 HH’s – Travel diary self-reported locations – GPS recorded trip files Parcel-level geographic reference – GIS shapefiles generated by MPO and individual counties (Fulton and Gwinnett Counties)

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 8 Example of GPS Trip Ends All GPS Trip-Ends in 13-County Region during travel diary survey period

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 9 Final Data Format Each location record has three associated coordinates – GPS trip-end point – Parcel centroid – Interpolated location (street network) Characteristics – Unique ID – Area – Land use – TAZ 40’ Centroid GPS Geocode w/ offset

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 10 Data Quality Issues – GPS/Diaries Travel diaries versus GPS trip- ends – Under-reporting of visited locations in travel diaries GPS wander – Dependent on weather, satellite, and hardware conditions – Primarily occurs at < 5 mph – Data point is last GPS coordinate at engine-off

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 11 Data Quality Issues – Reference GIS parcel boundaries and centroids – Not all parcels have existent or correct address data – Topology errors may lead to inaccurate centroid calculation Road network geocoding – Uses national database generated by NavTeq and TeleAtlas, may not have current/correct address ranges

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 12 The Incredible Shrinking Data Set Fulton: 195 locations, 119 unique Gwinnett: 129 locations, 75 unique Vehicle trips taken by survey participants (post-validity check) % Vehicle trips recorded by address in diary % Vehicle trips matched (diary to GPS, manually by timestamp) % Diary/GPS locations corresponding to available county GIS references % Diary/GPS locations with ‘correct’ address data (two counties) % Diary/GPS locations geocoded using nat’l road network database % Diary/GPS locations matched to parcels % Further QAQC based on trip-end distance and standard deviation yields… (note: miscoded GPS trips, should have been screened out earlier) % Data Sourcen% of set Two-county subset Metro Atlanta (13 counties +)

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 13 Analysis – Positional Accuracy Complete (3-source) data only: 324 points (194 unique) – 195 Fulton, 129 Gwinnett Compare – GPS trip-end data with parcel centroids – Interpolated addresses with parcel centroids – GPS trip-end data with interpolated addresses Further comparison according to – Land use – Parcel size (e.g. = 5 acres)

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 14 Positional Accuracy – GPS vs Geocode GPS significantly more accurate than geocoding – Combined: 273’ vs 402’ (Single-family) residential locations more accurate than non-residential parcels Smaller parcels more likely than larger parcels to have better positional accuracy for all methods

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 15 Positional Accuracy – Land Use / Size GPS to centroid accuracy has some correlation to parcel size, but land use and typical parking location are probably more important Within particular land uses, inverse relationship of accuracy to area

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 16 Results – Polygon Assignment Parcel and Blockgroup Match rates to potential TDM inputs – Parcels, Census Blockgroup

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 17 Results – Polygon Assignment Land Use and TAZ Match rates to potential TDM inputs – Land Use, Traffic analysis zone (TAZ)

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 18 Polygon Assigment Rate – TAZ Non-residential locations especially prone to mis- assignment InterpolationGPS Comm < 5 acres (n = 49) 83.7%91.8% Comm >= 5 acres (n = 38) 60.5%97.4% Industrial (n=16) 100.0% Office/Inst >= 5 acres (n=69) 63.6%72.7% Office/Inst < 5 acres (n=33) 77.8%72.2% Residential (n=148) 100.0%98.6% Park / Recreation (n=4) 75.0% TOTAL (n = 324) 86.4%91.7%

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL Discussion Reference Data – Must be accurate and standardized! Positional Accuracy – Method of creating geocoded data depends on degree of accuracy needed Most to least accurate ( 1000 away): Address matching, GPS, interpolation – Off-site parking creates issues for passive determination of trip purpose from GPS data 19

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL Discussion Polygon Assignment – TAZ “hit rate” lower than expected, particularly for non-residential locations – Degree of zoning homogeneity and size of parcels are directly proportional to chance of matching “correct” land use for TDM verification 20

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL Next Steps Assess method of GPS tracking and data gathering – Quantify error associated trip-ends Determine how to evaluate large parcels / campuses – Internal destinations, land uses 21

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 22 Any Questions? Please use the Microphone

COMMUTE Atlanta TRB Planning Applications Conference - May 2007, Daytona Beach, FL 23 Appendix: Sources and Additional Figures All figures created by Commute Atlanta researchers, except spatial interpolation picture (slide 5 from “Three Standard Geocoding Methods” – Dramowicz, 2004) and Google Earth imagery (slides10 and 21) Right: GPS position off due to urban canyon (tall buildings in Midtown Atlanta)