Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes

The use of winter cover crops and conservation tillage are agricultural practices promoted to reduce nutrient and sediment loss from cropland, improve soil health, increase infiltration, and support farm nutrient cycling and ecosystem services. However, environmental performance of these practices is variable in the working farm landscape. The Lower Chesapeake Bay research project within the USDA Long-Term Agroecosystem Research (LTAR) network has collaboratively developed satellite remote sensing algorithms to measure the performance and phenology of winter cover crops (aboveground biomass, nitrogen content, fractional cover, and emergence and termination dates) using no-cost Harmonized Landsat and Sentinel-2 multispectral satellite imagery. This research supports annual operational assessment of >28,000 fields per year in four states. Results document the impacts of agronomic management on conservation outcomes, support adaptive management of incentive payment structures, and can reduce the workload for conservation district staff by remotely verifying cover crop management. Additionally, super-spectral satellite applications have been developed to accurately map crop residue cover by measuring lignocellulose absorption in shortwave infrared wavelengths, producing a 7-year time series of tillage intensity maps for the Delmarva Peninsula. These remote sensing products can be used in decision support and modeling to estimate changes in nutrient, sediment, and carbon cycling resulting from conservation practice implementation in the working farm landscape. This manuscript provides an overview of remote sensing research findings and applications associated with the USDA LTAR and Conservation Effects Assessment Projects (CEAP), documenting a variety of previously published outcomes with update and expansion of techniques using additional unpublished data and analyses as appropriate.

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Publication Details

Journal
Journal of Environmental Quality
Published
2025-10-21
DOI
https://doi.org/10.1002/jeq2.70082
Citations
2
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
3.43

Funders

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article

Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes

Brian T. Lamb, Michael H. Cosh, Craig S. T. Daughtry, Gregory W. McCarty et al.
2 citations
Journal of Environmental Quality
Remote Sensing in Agriculture
3.43
article

Satellite assessment of winter cover crop and conservation tillage outcomes to support adaptive management in working landscapes

Brian T. Lamb, Michael H. Cosh, Craig S. T. Daughtry, Gregory W. McCarty, W. Dean Hively, Jyoti S. Jennewein, Alison Thieme, Cathleen J. Hapeman, Steven Brian Mirsky, Jason Keppler, Feng Gao, Xuesong Zhang
article en
2 citations

Abstract

The use of winter cover crops and conservation tillage are agricultural practices promoted to reduce nutrient and sediment loss from cropland, improve soil health, increase infiltration, and support farm nutrient cycling and ecosystem services. However, environmental performance of these practices is variable in the working farm landscape. The Lower Chesapeake Bay research project within the USDA Long-Term Agroecosystem Research (LTAR) network has collaboratively developed satellite remote sensing algorithms to measure the performance and phenology of winter cover crops (aboveground biomass, nitrogen content, fractional cover, and emergence and termination dates) using no-cost Harmonized Landsat and Sentinel-2 multispectral satellite imagery. This research supports annual operational assessment of >28,000 fields per year in four states. Results document the impacts of agronomic management on conservation outcomes, support adaptive management of incentive payment structures, and can reduce the workload for conservation district staff by remotely verifying cover crop management. Additionally, super-spectral satellite applications have been developed to accurately map crop residue cover by measuring lignocellulose absorption in shortwave infrared wavelengths, producing a 7-year time series of tillage intensity maps for the Delmarva Peninsula. These remote sensing products can be used in decision support and modeling to estimate changes in nutrient, sediment, and carbon cycling resulting from conservation practice implementation in the working farm landscape. This manuscript provides an overview of remote sensing research findings and applications associated with the USDA LTAR and Conservation Effects Assessment Projects (CEAP), documenting a variety of previously published outcomes with update and expansion of techniques using additional unpublished data and analyses as appropriate.

Journal of Environmental QualityVol. 54(6)
United States Geological Survey (US), Agricultural Research Service (US), Maryland Department of Natural Resources (US), Beltsville Agricultural Research Center (US)
National Aeronautics and Space Administration, U.S. Department of Agriculture, Nuclear Safety and Security Commission, U.S. Geological Survey
Openalex Percentile: Top 7%
Remote Sensing in Agriculture
3.43
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