Site-Specific Precision Cover Cropping for Soil Health and Environmental Sustainability Using Remote Sensing and Multi-Criteria Analysis

ABSTRACT Cover crops, which are plants or mixtures of plants grown primarily to enhance and protect soil health, are a key strategy in sustainable agriculture. Traditionally, they have been uniformly planted in a field typically during off-season when the main crops are not in competition. However, advancements in precision agriculture, particularly the integration of remote-sensing technology, demand more efficient seeding strategies based on field variability. The aims of this study were to assess the specific needs of a field in Aurora County, SD, and determine the type and optimal combinations of the cover crop mix. The cover crop species considered in this study included legumes, grasses, and brassicas. The remote-sensing data were extracted from Sentinel-2 satellite imagery. Soil samples were collected from 0 to 30 cm depth, and soil properties were measured. Additionally, topographic maps such as slope and aspect were extracted from light detection and ranging (LiDAR) data. The results of precision cover crop analyses showed that 6.5 percent (7.8 ha), 20.6 percent (24.7 ha), 38.1 percent (45.7 ha), 29.6 percent (35.5 ha), and 5.3 percent (6.3 ha) of the studied field should planted in the following mixtures of crops: rye, radish, and vetch; triticale, turnip, and vetch; triticale, radish, and clover; triticale, rapeseed, and pea; and barley, flax, and clover, respectively. The mixtures significantly improved soil properties by reducing compaction, increasing residue C/N ratio, and enhancing weed suppression compared with the control. The resulting map should be interpreted as a decision-support recommendation rather than a fully validated field prescription.

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Publication Details

Journal
Environmental and Engineering Geoscience
Published
2026-10-13
DOI
https://doi.org/10.21663/eeg-d-26-00041
Primary Topic
Soil Management and Crop Yield
Type
article
Field-Weighted Citation Impact
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article

Site-Specific Precision Cover Cropping for Soil Health and Environmental Sustainability Using Remote Sensing and Multi-Criteria Analysis

Salman Mirzaee, Ali Mirzakhani Nafchi
Environmental and Engineering Geoscience
Soil Management and Crop Yield
article

Site-Specific Precision Cover Cropping for Soil Health and Environmental Sustainability Using Remote Sensing and Multi-Criteria Analysis

Salman Mirzaee, Ali Mirzakhani Nafchi
article en

Abstract

ABSTRACT Cover crops, which are plants or mixtures of plants grown primarily to enhance and protect soil health, are a key strategy in sustainable agriculture. Traditionally, they have been uniformly planted in a field typically during off-season when the main crops are not in competition. However, advancements in precision agriculture, particularly the integration of remote-sensing technology, demand more efficient seeding strategies based on field variability. The aims of this study were to assess the specific needs of a field in Aurora County, SD, and determine the type and optimal combinations of the cover crop mix. The cover crop species considered in this study included legumes, grasses, and brassicas. The remote-sensing data were extracted from Sentinel-2 satellite imagery. Soil samples were collected from 0 to 30 cm depth, and soil properties were measured. Additionally, topographic maps such as slope and aspect were extracted from light detection and ranging (LiDAR) data. The results of precision cover crop analyses showed that 6.5 percent (7.8 ha), 20.6 percent (24.7 ha), 38.1 percent (45.7 ha), 29.6 percent (35.5 ha), and 5.3 percent (6.3 ha) of the studied field should planted in the following mixtures of crops: rye, radish, and vetch; triticale, turnip, and vetch; triticale, radish, and clover; triticale, rapeseed, and pea; and barley, flax, and clover, respectively. The mixtures significantly improved soil properties by reducing compaction, increasing residue C/N ratio, and enhancing weed suppression compared with the control. The resulting map should be interpreted as a decision-support recommendation rather than a fully validated field prescription.

Environmental and Engineering Geoscience
South Dakota State University (US)
Openalex Percentile: Top 15%
Soil Management and Crop Yield
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