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The PECAS Land Use Modelling System

This presentation from the World Symposium on Transport and Land Use Research 2014 explores the PECAS Land Use Modelling System, presented by notable experts John Abraham, Geraldine Fuenmayor, JD Hunt, and Eric Miller. PECAS offers a generalized approach to land use forecasting, focusing on five interrelated decisions in spatial choice. This system integrates transportation and land use dynamics, providing valuable insights for planners and researchers interested in effective land use strategies and their implications on urban development.

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The PECAS Land Use Modelling System

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  1. The PECAS Land Use Modelling System

    World Symposium on Transport and Land Use Research 2014 Slides by John Abraham, Geraldine Fuenmayor, JD Hunt Presented by Eric Miller
  2. PECAS Generalized system for land use forecasting Abstracts five interrelated decisions in spatial choice: Location What to make and what to consume (“technology” or “lifestyle”) Where to buy what is consumed and where to sell what is made And two interrelated decisions in space construction: What type of space (floorspace, buildings) to build, if any How much space to build (intensity)
  3. Motivational Theory “Businesses, Households, Firms, Institutions, etc, like to locate in locations that are well-positioned for the interactions that they choose to undertake” von Thünentheory generalized to account for endogenous prices, random utility, multiple markets, multiple products, consumption together with production “Developers like to build things that will generate profitable income streams” Basic real estate theory combined with random utility theory.
  4. PECAS AA Choice Model Additive logit theory Location Choice location alternatives; building with local and neighbourhood attributes Technology Choice technology options; vectors of the make and use of items, production processes for establishments and lifestyles for households Buying and Selling Exchange Choice exchange locations; where the seller stops and the buyer starts paying for transport
  5. Goods, Services, Labour and Space $ $ $ $ $ $ $ Producing Sectors $ $ $ $ $ $ $ $ $ Economic Flows $ $ $ $ $ $ Consuming Sectors $ $ $ $ $ $ $ $ $ $ $ $ $
  6. no change more the same mid density residential commercial industrial derelict Quantity (Continuous) Space Development: Simulation of Transitions parcel-by-parcel microsimulation Joint continuous/discrete logit theory zoning dictates set of alternatives
  7. PECAS
  8. Data considerations Input/Output economic data, Regional economic profile, Regional economic forecast. Represent all monetary interactions in PECAS Land cover data (cadastral data) and land characteristics (PECAS has systems to deal with errors/inconsistencies) Travel demand model Historical development and location choices Past census Development permits/construction Location rent data (real estate listings, property tax assessments) Transportation costs and choices (e.g. travel survey)
  9. PECAS Software Environment Java executable for core modules AA and SD Multithreaded, stable, tested, fast Python scripts run modules in turn through simulation time Easily customizable, integrates into legacy systems PostGIS spatial database of inputs and outputs Easily integrates with GIS systems and other software MapIt browser-based data explorer/selector/visualizer/exporter UI for analysts Calibration scripts, routines Mostly python, some database views and excel sheets
  10. Other PECAS Resources Demonstration model download and install Complete model including software and data distributed under Apache V2.0 License Based on Baltimore model Modellers’ PECAS Wiki at hbaspecto.com HBA Specto Incorporated staff Consulting firms including Parsons Brinkerhoff Researchers/Professors at other universities Dimantha De Silva University of Moratuwa Sri Lanka Michael Clay Bringham Young University Utah Caroline Rodier, UC Davis ULTRANS California
  11. PECAS Applications Atlanta California (Statewide) Oregon (Statewide) Baltimore Sacramento Alberta (Province) Caracas San Diego, CA California (Statewide) Los Angeles Also used partially or under development in Mumbai Edmonton Ohio (Statewide) Montgomery, AL
  12. Some policy results results San Diego: Our negotiated land use plan doesn’t perform as well as allowing more density near the waterfront where everyone wants to live Benefit of best transportpolicy Benefit of abandoning previous land use plan
  13. Removing Household Capacities 150kplus 3+ households
  14. Atlanta: We need to give multifamily developers more opportunities to build in central areas or TOD areas, or else we’ll need to build transportation systems to emerging distant suburban nodes
  15. Households Baltimore: Our long term transportation infrastructure plans are almost worthwhile from a cost-benefit analysis Benefit measures Industry Quietly adjust and fine tune the plan (e.g. complementary land use policies) to ensure benefit/cost > 1.0
  16. Oregon: Program $Billions in bridge repair to be affordable and favour critical industries and locations
  17. Los Angeles: Allowing higher density near certain transit nodes will, by itself, lead to only modest amounts of transit oriented development. Percent change in households
  18. Conclusions PECAS is a practical forecasting and policy analysis tool grounded in basic accepted theories. Although simple in concept, it supports a wide variety of analysis, and requires a large investment in data, development, and calibration. Used for both forecasting and policy analysis. Your favourite policies may be shown to be less effective than you hoped! in the long run such a realization seems to lead to better policies for a region.
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