H-GAC’s Forecast as “Production” Operations: General Organization, Logistics, and Schedules...
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Transcript of H-GAC’s Forecast as “Production” Operations: General Organization, Logistics, and Schedules...
![Page 1: H-GAC’s Forecast as “Production” Operations: General Organization, Logistics, and Schedules Dmitry Messen Houston-Galveston Area Council.](https://reader035.fdocuments.in/reader035/viewer/2022072015/56649ebb5503460f94bc3819/html5/thumbnails/1.jpg)
H-GAC’s Forecast as “Production” Operations: General Organization,
Logistics, and Schedules
Dmitry MessenHouston-Galveston Area Council
![Page 2: H-GAC’s Forecast as “Production” Operations: General Organization, Logistics, and Schedules Dmitry Messen Houston-Galveston Area Council.](https://reader035.fdocuments.in/reader035/viewer/2022072015/56649ebb5503460f94bc3819/html5/thumbnails/2.jpg)
Overview• Forecasts: 1972, 1986, 1992, 2003, 2006• Breaking up with the RTP cycle• Beginning in April 2013: Quarterly Releases– Annual data 2010-2040– Population, Employment: TAZ, CT, County, Region– Land use (type, sqft, HU): parcel
• Current, Announced Changes, Model Predictions
• No “adoption” process, no drafts/preliminaries• (de facto Public) continuous external/internal
Review focused on detection of factual “errors” (QA/QC)
![Page 3: H-GAC’s Forecast as “Production” Operations: General Organization, Logistics, and Schedules Dmitry Messen Houston-Galveston Area Council.](https://reader035.fdocuments.in/reader035/viewer/2022072015/56649ebb5503460f94bc3819/html5/thumbnails/3.jpg)
2-Phase Forecasting System• Demographic Microsimulation– Population regional “totals”– Net change in households (demand for housing)– Labor force Workforce Jobs (demand for non-
res sqft)• Land Use Microsimulation– Aggregate demand List of Projects– Development Proposals Selection on ROI
Buildings• 3rd Phase (not yet implemented)– Household and job location choice
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LU Data Development• Continuous, never ending process• Independent from model development and
model execution• Labor-intensive and code-intensive• Requires smart and flexible design of workflows
and data architecture• No way around it
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Dynamic Land Use• Corrections to Current LU (existing buildings)– Why live with errors? Why not keep corrections?
• Announced Projects– Regionally-significant (e.g., new Exxon’s campus)– Locally-significant
• Sources– Imagery, Google’s StreetView– Plats (ordered from counties 4 times a year)– Business media– Appraisal (once a year)
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Parcels and Buildings• Create and maintain our own polygons (“Master
Polygons”) and buildings• From land ownership parcels to polygons that are– Positionally accurate– Comprehensive (100% coverage)– Integrated (land, water, roads)– Meaningful (single polygon for a park, downtown
block, mall, etc)• Detect annual changes in parcels and apply them
to “Master Polygons”
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Parcels and Buildings• Keep dynamic info (valuations, rents) separate
from static info (type, sqft, floors)• Tie-backs to appraisal records• Land Use data (GIS: feature classes and tables)• Create from Land Use data (+ other data)– Inputs for model simulation– Inputs for model estimation (we do not re-
estimate the model every quarter)
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Non-LU Inputs• ACS Summary Tables, ACS PUMS, BEA, BLS• Once a year, but schedules are different• There’s always some update that we can include
in a quarterly release• Efficient process, takes minimal time– download, run SAS code
• Supports Currentness– Latest Planning Assumptions (Fed regs)
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Decoupling of Production and R&D
• Production– Product (Forecast) is always available– Updated/Upgraded quarterly– Releases are labeled (2014Q1, 2014Q2,…)
• R&D– Model changes– New components
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Distribution and Review• Distribution– Table query tool; download xls– Web-based mapping app (RLUIS); download GIS
data– Map service
• Review– Parcel-specific feedback directly from RLUIS (also
TAZ and CT)– General comments
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Staffing (8)• Manager• Senior Modeler (LU)• Senior GIS Analyst (Data Development)– 2 GIS Analysts and 1 GIS Technician
• Senior Analyst (Tools, Technology, Infrastructure)– 1 GIS Analyst/Programmer
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Lessons• Credibility of our work hinges on the accuracy of
the current land use and development “pipeline” data
• Enormous potential for other applications– Community planning, public health, environmental
• Benefits of transparency and openness• Challenges (difficult=interesting)– Design of workflows and procedures– Technology (SDE, network, web)– Distractions; escalating expectations
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