I have been struck lately by the progress of several projects using non-ESRI based GIS planning support systems and how often the decision to move away from ESRI has been that PC based ArcGIS cannot handle the large data sets for real-time scenario analysis. I just saw a beta demonstration of a wildfire mitigation application developed by the University of Colorado's Planning department that uses a combination of open source GIS, SQL server, and Perl coding to help cities and counties look at alternative growth futures and how they impact fire mitigation.
I have been struck lately by the progress of several projects using non-ESRI based GIS planning support systems and how often the decision to move away from ESRI has been that PC based ArcGIS cannot handle the large data sets for real-time scenario analysis.
I just saw a beta demonstration of a wildfire mitigation application developed by the University of Colorado's Planning department that uses a combination of open source GIS, SQL server, and Perl coding to help cities and counties look at alternative growth futures and how they impact fire mitigation. While the department has been working on the modeling component for a couple of years, developing the internet-based GIS interface took them about 6 months. I was particularly struck by the speed of analysis. Which revived a question I have been thinking about from time to time: Will ESRI be able to keep up with Internet based mapping solutions?
An Internet version of PLACE3S (I-PLACE3S), which utilizes powerful database servers to do its analysis, has enabled the Sacrament Area Council of Governments (SACOG) to work with very large data sets with more than 600,000 parcels and generate results on the scenarios being discussed as part of their Sacramento Region Blueprint: Transportation/Land Use Study (http://www.sacregionblueprint.org/sacregionblueprint/).
A couple years back the PC version of PLACE3S which ran on ArcView took hours to run and was getting bogged down with large data sets. The California Energy Commission which has helped support the development of PLACE3S (http://www.energy.ca.gov/places/) turned to EcoInteractive, Inc. to help develop an internet version that utilized Oracle databases for analysis. I-PLACE3S brought the analysis time down to a few seconds. This high speed analysis helped avoid "dumbing down" the data to more summary aggregations of data while ensuring the public does not get restless in workshops... or city council in hearings! Also, because I-PLACE3S is offered over a server, SACOG has one copy of the programming to keep up to date and oversee for quality control. The public can upload their data to the secure server and nobody can access their data, which they like for security and quality control. Each user can customize the formulas inside I-PLACE3S so that they accurately address local issues e.g., cost of housing, demographics, vehicle fleet characteristics, etc. I-PLACE3S provided real-time feedback so that, through an iterative process, the amateur planners could see for themselves how every decision they made might play-out over the next 50 years. By combining visualization, GIS modeling techniques, and impact analysis, I-PLACE3 helped SACOG engage the public in well-informed discussions about preferred future land use and transportation plans.
Another example of using a non-ESRI based GIS planning support system, is in Mammoth Lakes, CA where the Town partnered with Facet (http://www.facet.com) to develop an interactive, publicly accessible website that uses an underlying scenario based land use model to demonstrate the tradeoffs inherent in strategic planning policies. Public access to the tool is founded on the actual parcel, zoning, infrastructure and natural landscape data that the planners use to support their day-to-day decision making. The tool integrates diverse topics such as air quality, building height traffic congestion, tax revenues, sprawl, public safety and water infrastructure capacity and allows the user to explore tradeoffs between them by making policy selections and seeing how those impact key indicators.

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