Remote Sensing - Based Mapping and Analysis of Winter Cover Crop Adoption for Sustainable Agriculture, Minnehaha County

Winter cover crops planted by farmers such as cereal rye, crimson clover, radishes, hairy vetch, and winter wheat are used to conserve and protect the soil during winter. These crops offer numerous benefits such as improving soil health, reducing erosion, fixing nitrogen, increasing carbon sequestration, and weed suppression. Over time, winter cover cropping has been recognized as a sustainable agricultural practice and has gained attention from Federal and State conservation programs, farmers, and non-governmental organizations. Due to their vital benefits, agencies such as the United States Department of Agriculture (USDA), Natural Resources Conversation Services (NRCS) have partnered with cost-share programs like the Environmental Quality Incentives Program (EQIP) and Conservation Stewardship Program (CPS) to encourage adoption of cover cropping as a sustainable agricultural practice. While previous studies have explored cover crops in various aspects, few have analyzed the recent adoption trend of winter cover crops. With advancements in remote sensing and machine learning, this study aimed to map and analyze the recent adoption of winter cover crops over a six-year period from (2018-2023) in Minnehaha County. A Random Forest machine learning model was trained to generate annual winter cover crop maps, which was then used to assess the recent adoption trend within the county. Additionally, a hot spot analysis was conducted to identify the clustering patterns. The study utilized data from Sentinel-2 (10m), the United States Cropland Data Layer (CDL) (30m), and ground truth crop field data samples. The outcome of this research is to provide a comprehensive understanding of the recent adoption of winter cover crops. The research findings could provide valuable information that could be used to assist in informing and guiding sustainable agricultural policies and decisions towards the adoption of winter cover crops.

Publication Details

Journal
Open PRAIRIE (South Dakota State University)
Published
2025-01-01
Primary Topic
Cell Image Analysis Techniques
Type
article
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article

Remote Sensing - Based Mapping and Analysis of Winter Cover Crop Adoption for Sustainable Agriculture, Minnehaha County

Open PRAIRIE (South Dakota State University)
Cell Image Analysis Techniques
article

Remote Sensing - Based Mapping and Analysis of Winter Cover Crop Adoption for Sustainable Agriculture, Minnehaha County

article en

Abstract

Winter cover crops planted by farmers such as cereal rye, crimson clover, radishes, hairy vetch, and winter wheat are used to conserve and protect the soil during winter. These crops offer numerous benefits such as improving soil health, reducing erosion, fixing nitrogen, increasing carbon sequestration, and weed suppression. Over time, winter cover cropping has been recognized as a sustainable agricultural practice and has gained attention from Federal and State conservation programs, farmers, and non-governmental organizations. Due to their vital benefits, agencies such as the United States Department of Agriculture (USDA), Natural Resources Conversation Services (NRCS) have partnered with cost-share programs like the Environmental Quality Incentives Program (EQIP) and Conservation Stewardship Program (CPS) to encourage adoption of cover cropping as a sustainable agricultural practice. While previous studies have explored cover crops in various aspects, few have analyzed the recent adoption trend of winter cover crops. With advancements in remote sensing and machine learning, this study aimed to map and analyze the recent adoption of winter cover crops over a six-year period from (2018-2023) in Minnehaha County. A Random Forest machine learning model was trained to generate annual winter cover crop maps, which was then used to assess the recent adoption trend within the county. Additionally, a hot spot analysis was conducted to identify the clustering patterns. The study utilized data from Sentinel-2 (10m), the United States Cropland Data Layer (CDL) (30m), and ground truth crop field data samples. The outcome of this research is to provide a comprehensive understanding of the recent adoption of winter cover crops. The research findings could provide valuable information that could be used to assist in informing and guiding sustainable agricultural policies and decisions towards the adoption of winter cover crops.

Open PRAIRIE (South Dakota State University)
Zero hunger
Openalex Percentile: Top 47%
Cell Image Analysis Techniques
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