A Comprehensive Parcel-Level Dataset on Farmland Assessment: Addressing Grid-Cell Data Bias Estimation

Wai Yan Siu (), Man Li and Arthur Caplan
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Wai Yan Siu: Institute for Coastal Adaption and Resilience (ICAR), Old Dominion University, 800 W. 46th St., Norfolk, VA 23508, USA
Man Li: Department of Applied Economics, Utah State University, Logan, UT 84322, USA

Data, 2025, vol. 10, issue 1, 1-12

Abstract: Grid-cell data are increasingly used in research due to the growing availability and accessibility of remote sensing products. However, grid-cell data often fails to represent the actual decision-making unit, leading to biased estimates in socio-economic analysis. To this end, this paper presents a comprehensive parcel-level dataset for Salt Lake County, Utah, spanning from 2008 to 2018. This dataset combines detailed spatial and temporal data on land ownership, land use, and preferential farmland tax assessments under the Greenbelt program. Compiled from multiple geospatial sources, the dataset includes nearly 200,000 parcel-year observations, providing valuable insights into landowner decision-making and the impact of tax abatement incentives at the decision-making level. This resource is beneficial for researchers, educators, and practitioners in sustainable development, environmental studies, and farmland conservation.

Keywords: agricultural land protection; land use change; land use policy; preferential tax assessment (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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