PLACES-FMV (CONUS)

Note

This is a draft document to facilitate communications with the research team, collaborator panel, data partners, and early data adopters. Please report errors to chrnolte@bu.edu.

This is the documentation and user’s guide for PLACES-FMV (CONUS).

PLACES-FMV (CONUS) is a data volume of parcel-level estimates of the “fair market value” (FMV) of vacant and mostly-vacant lands in the contiguous United States (CONUS).

These estimates were produced by statistical models trained on price data of millions of property transactions (2000-2021) linked to parcel boundaries and public predictor data.

The research is conducted by the PLACES lab at Boston University with support from the National Science Foundation (NSF) [1].

Overview

• About
  • People
  • PLACES
• Data
  • Parcels
  • Transactions
  • Predictors
• Methods
  • Estimation
  • Validation
• Results
  • Data products
  • Publications

Footnotes

[1]

Award #2149243, Human-Environment and Geographical Sciences, National Science Foundation (NSF). PLACES is also supported by NSF’s “Coastlines and People” program (#2209190) and the National Aeronautics and Space Administration’s (NASA) Water Resources Applications program (#21-WATER21-2-0027). In the past, we have received research support from The Nature Conservancy and Boston University’s Rafik B. Hariri Institute for Computing and Computational Science and Engineering.

Note

Data for the first phase of this research (Aug 1, 2022 - Sep 30, 2023) provided by Zillow through the Zillow Transaction and Assessment Dataset (ZTRAX). More information can be found at http://www.zillow.com/ztrax. The results and opinions are those of the author(s) and do not reflect the position of Zillow Group.

Note

We thank Regrid’s Data with Purpose program, which provides access to nonprofit researchers on a “pay what you can” basis. For two thirds of CONUS counties, PLACES-FMV (CONUS) is based on Regrid parcel data. For the remaining counties, parcel boundary data was downloaded from publicly available sources.

Important

The data comes without any legal warranties or formal guarantees (other than it has been produced with the data and methods outlined here). Errors in data entry, processing, and interpretation are bound to occur when public records and satellite data are synthesized and interpreted across a vast and incredibly diverse continent.

Important

All data shared inherit the data use licenses from the most conservative of their input sources (see Data). We are working on an agreement that allows us to share our final data volume at no cost with government, academic, and non-profit analysts through the Inter-university Consortium for Political and Social Research (ICPSR).