Remote sensing of conservation practices: Do expired Conservation Reserve Program fields continue to provide environmental benefits?

Authors: Timothy Assal*, Kent State University, Mark W. Vandever, United States Geological Survey, Sarah K Carter, United States Geological Survey, Richard Iovanna, United States Department of Agriculture, Farm Service Agency
Topics: Natural Resources, Remote Sensing, Agricultural Geography
Keywords: agriculture, remote sensing, Conservation Reserve Program, ecosystem benefits
Session Type: Virtual Paper
Day: 4/9/2021
Start / End Time: 1:30 PM / 2:45 PM
Room: Virtual 22
Presentation File: No File Uploaded


Since 1985 the Conservation Reserve Program (CRP), administered by the U.S. Department of Agriculture, has allocated funds to private landowners in exchange for implementation of conservation practices. Initially, the CRP targeted marginal cropland for soil conservation, however, it has since been recognized for provision of additional benefits such as water quality, erosion control, wildlife habitat, and carbon sequestration. However, land tenure in the CRP program fluctuates and there is little information on the environmental services provided by these fields after the CRP contract expires. The goal of this project is to assess the environmental benefits of conservation practices on expired CRP lands in agroecosystems across the Great Plains.

We conducted edge-of-field surveys to document the status of expired CRP fields and compared this data with the USDA Cropland Data Layer. We also developed randomForest models of perennial and agriculture cover using a combination of Landsat-derived phenological variables in Google Earth Engine.

Here we present the results from a subset of our study in Colorado, where we found that 57% of expired CRP fields remained in grass cover after the contract with USDA expired. The Cropland Data Layer correctly classified nearly 70% of the expired fields remained in grass cover and were not converted back to crops. Initial results from our modeling approach show high levels of agreement between ground and satellite data. We will compare results from both approaches and address the potential application of this open data framework to link remote sensing data with conservation practices.

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