Data for: High-resolution land value maps reveal underestimation of conservation costs in the United States

The justification and targeting of conservation policy rests on reliable
measures of public and private benefits from competing land uses. Advances
in Earth system observation and modeling permit the mapping of public
ecosystem services at unprecedented scales and resolutions, prompting new
proposals for land protection policies and priorities. Data on private
benefits from land use are not available at similar scales and
resolutions, resulting in a data mismatch with unknown consequences. Here
I show that private benefits from land can be quantified at large scales
and high resolutions, and that doing so can have important implications
for conservation policy models. I develop the first high-resolution
estimates of fair market value of private lands in the contiguous United
States by training tree-based ensemble models on 6 million land sales. The
resulting estimates predict conservation cost with up to 8.5 times greater
accuracy than earlier proxies. Studies using coarser cost proxies
underestimated conservation costs, especially at the expensive tail of the
distribution. This might have led to underestimations of policy budgets by
factors of up to 37.5 in recent work. More accurate cost accounting will
help policy makers acknowledge the full magnitude of contemporary
conservation challenges, and can assist with the targeting of public
ecosystem service investments.