gis research needs

Wende Mix, Buffalo State College

GIS Research Needs

Strategic Planning


Crystal Ball Metaphor

GIS Research Committee wants us to GAZE INTO THE FUTURE

Anticipate and plan for new technologies and applications

Strategic Planning

Anticipate and plan for growing, decreasing, or changing travel demands

Forecast infrastructure needs plan operations, address practices and policies


Crystal Ball

Metaphor

Simulation/ scenariosCause and effect relationshipsTrends (historical data)Spatial AnalysisPredictionGraphical Output

TransportationStrategic Planning


• GIS-T Research VisionBack to the future

• GIS-T Research Mission– Encourage and champion research, – training, and – information dissemination and sharing

Strategic Planning


Critical Issues• DOTs, MPOs, & other agencies have

spent over a decade amassing huge amounts of very detailed spatial data and building Linear Referencing Systems (LRS)

• Planners use vast amounts of demographic and socio-economic data

• Data models mostly center on Census geography and transportation analysis zones (TAZs)

• What about parcels, individual locations (GPS)?

• What about neighborhoods, planning communities?


Critical Issues• New data sources

– American Community Survey (ACS)– Establishment data (LEHD)

• Visualization, data quality, documentation of uncertainty (accuracy)

• ACS 5 year average data• Estimates have upper and lower bounds

How do we visually communicate that some tracts, TAZs, etc have values that are not statistically significantly different?

• Tract A has 120 (+ 10) households with 0 vehicles (110, 130)

• Tract B has 95 (+ 15) households with 0 vehicles (80, 110)

• Class ranges areO-5051-100101-150151-200201 +


Critical Issues• New data sources

– American Community Survey (ACS)– Establishment data (LEHD)


• Does establishment data accurately represent where workers work?

– Headquarters, administrative offices, multi-units– Workers from out of state– Workers who work out of state

• Can parameters be established that characterize the accuracy of aggregate workplace locations from establishment (or Census) data?


Critical Issues• Geocoded data


• How accurate is it?

• How can it be improved?

• How do we document its quality?


Air photos, parcels, TIGER

All projected to State Plane, NAD 83 (feet), NYS West


Street Centerline Model• Model of last resort!• Fraught with positional and representational

inconsistencies– E.g. No addresses on east side of street– Addresses don’t exist along entire range (continuum)– Nodes (beginning/ending) location and parcel locations

don’t coincide– Databases inaccurately represent jurisdictional

boundaries• Search algorithms rely heavily on accurate zip

code and jurisdiction data.• More effective for navigational purposes than

representing land use or reflecting human perception


Address data

• How good is it?– Train people to collect better data– Train people to use GIS capabilities to QC the data

• Consider the source– Crime locations

• From police records

– Real estate transactions• Deeds of records (County clerk’s office)

– Travel Survey Data!!!!!!!!!!!!!!!!• Many sources of error

• Document the accuracy (Methods?)


Original Crime DatasetJan – July 2005

Buffalo, NY37487 Records

Unique Crime Calls21764 records

Locations with a street address18545 records (85%)

Locations with Intersection/place name3219 records (15%)

Locations withStreet name in Parcel database

18181 records (98%)

Locations withoutStreet name in Parcel database364 records (2%)

Batch match toParcel database

13722 records (75%)

No match toParcel database

4459 records (25%)

Batch match toStreetmap database4087 records (92%)

Interactive match toStreetmap database

372 records (8%)


Interactive match toStreetmap database637 records (20%)

Geocoding Accuracy SummaryMost accurate level possible – 16495 (76%)Including secondary batch match – 20582 (95%)Need manual intervention – 1182 (5%)


Interactive match toStreetmap database173 records (48%)

Documenting AccuracyUsing Two Tiered Geocoding


GBNRTC Household Travel Survey 2002Buffalo, NY

15969 Location Records

Reported City = Buffalo3947 records (25%)

Location Type = Home1033 records (26%)

Location Type = Work827 records (21%)

Zip code in Buffalo784 records (76%)

Zip code not in Buffalo249 records (24%)

No Street Address4 records (0.5%)

Street Name inParcel database574 records (73%)

Geocoding Accuracy SummaryHome Addresses - BuffaloMost accurate level possible – 830 (80%)Including secondary batch match – 994 (96%)Need manual intervention – 35 (4%)

Batch match toStreetmap

193 records (94%)(5 in Buffalo)

Location Type = School205 records (5%)

Location Type = Trip End1882 records (48%)

Street Name not inParcel database206 records (26%)

Street Name inParcel database52 records (21%)

Street Name not inParcel database197 records (79%)

Batch match toParcel database445 records (78%)

No match toParcel database129 records (22%)

Batch match toParcel database

7 records (13%)

No match toParcel database45 records (87%)

Manual Intervention

13 records (6%)


122 records (95%)(40 in Buffalo)

Manual Intervention7 records (5%)


185 records (94%)

Manual Intervention

12 records (6%)


42 records (93%)

Manual Intervention3 records (7%)


Bad Data makes Bad Models

• Focus on data quality– Preventing reporting

errors– Finding and correcting

errors– Documenting accuracy– Understanding error

propagation through models

gis research needs

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