Expanding the coverage and accuracy of parcel-level land value estimates

Area of Science:

• Conservation Science
• Environmental Economics
• Geospatial Analysis

Background:

• Cost-effective conservation planning hinges on high-resolution land cost data.
• Undeveloped land, often targeted for conservation, faces conversion pressures, particularly for agriculture.
• Existing models, like Nolte (2020), provide county and parcel-level estimates but can be enhanced.

Purpose of the Study:

• To improve the accuracy of undeveloped land value estimation for conservation.
• To incorporate agricultural productivity and regional market factors into land valuation models.
• To assess the cost-saving potential of enhanced land valuation for large-scale conservation initiatives.

Main Methods:

• Developed an enhanced land valuation model incorporating countywide median home value, climatic variables, and parcel-level soil data.
• Expanded the geographical scale of modeling to align with regional agricultural markets.
• Simulated the cost-effectiveness of a 30 percent land protection initiative using the enhanced model.

Main Results:

• The enhanced model achieved approximately 15 percent greater accuracy compared to a restricted benchmark.
• The improved modeling approach extended coverage to an additional 376 counties.
• Simulations indicated potential annual savings of approximately $15 million for a 30x30 initiative.

Conclusions:

• Accounting for agricultural productivity and regional market scales significantly improves land value predictions for conservation.
• The enhanced modeling strategy offers substantial cost savings for government land purchasing programs.
• This approach provides a more robust framework for cost-effective land conservation planning.