Clients
Spatial Data Processing Case Studies
TKT STPR iPhone & Android App helps avoid parking tickets in San Francisco
Challenge
General Eyeballs was in process of developing an iPhone & Android application to help drivers avoid parking tickets in San Francisco as well as other major urban centers. No central database of citywide parking regulations and restrictions in San Francisco existed so one had to be created that could intelligently integrate sophisticated spatial and non-spatial data.
Solution
Farallon Geographics integrated a variety of data sources from the City of San Francisco including point datasets for parking meter locations and non-spatial (i.e. tabular) datasets such as time restrictions and street cleaning schedules using sophisticated geospatial processing techniques to correctly position all the data on the right street segment and on the correct side of the street.
Voter record point data against a census block polygon layer
DNC National Election Precincts Dataset Development for 2008 Presidential Campaign
Challenge
Map the Vote, working with data from the Democratic National Committee (DNC) wanted to create a national election precinct GIS. But the costs and time required to produce the precincts layers using traditional GIS drawing methods were cost and time prohibitive.
Solution
Farallon developed automated geodatabase techniques and spatial analysis algorithms to process and validate millions of voter records. This enables organizations to cost-effectively microtarget voter turnout efforts for the 2008 Presidential campaign.
ISO Innovative Analytics risk management geoprocessing using Oracle Spatial
Challenge
ISO Innovative Analytics, a risk management insurance company, wanted to analyze massive amounts of unstructured historical data (both spatial and non-spatial ) in order to develop a flexible, customized and configurable nationwide set of potential risk factors. This would be used to improve the way insurance companies currently rate auto insurance policies.
Solution
Farallon developed a series of pre-processing services and custom data structures for the intensive geoprocessing using Oracle Spatial 10g. Tens of millions of individual policy locations were combined with historical claims records to determine predictive correlations between potential risk factors and location of policy holders.