Estimation of winter soil cover by vegetation before spring-sown crops for mainland France using multispectral satellite imagery

Nowak, Benjamin; Marliac, Gaëlle; Michaud, Audrey

doi:10.1088/1748-9326/ac007c

Cited by 12 publications

(10 citation statements)

References 32 publications

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“…This dataset provides an estimate of winter soil cover before spring crops at municipality level for mainland France for two years (2018 and 2019). It has been used to evaluate the effect of crop rotation [1] or soil and climatic conditions [2] on the adoption of winter cover crops in France.…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Dataset about the adoption of winter cover crops at the municipality level for mainland France

2022

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Dataset about the adoption of winter cover crops at the municipality level for mainland France

2022

Self Cite

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“…For France, maps of vegetated winter soil cover prior to the establishment of a spring crop were previously produced for years 2018 and 2019 (Nowak et al 2021). For each year, vegetation monitoring was carried out for two months (December and January) during the winter before sowing the spring crop.…”

Section: Estimation Of Winter Soil Cover Through Sentinel-2 Multispec...mentioning

confidence: 99%

“…Such soil coverage is easily detected on multispectral satellite images by computing vegetation indices such as the Normalized Difference Vegetation Index (NDVI). For the NDVI calculated from these images, a threshold of 0.52 can be considered as corresponding roughly to a 50% soil coverage by vegetation (Nowak et al 2021). For comparison, bare soils are generally characterized by NDVI values of about 0.2. of France's acreage under spring crops without NDVI extraction in 2018 and 2019, respectively).…”

Section: Estimation Of Winter Soil Cover Through Sentinel-2 Multispec...mentioning

confidence: 99%

“…For comparison, bare soils are generally characterized by NDVI values of about 0.2. of France's acreage under spring crops without NDVI extraction in 2018 and 2019, respectively). Additional information about the NDVI extraction procedure can be found in the study by Nowak et al (2021).…”

Section: Estimation Of Winter Soil Cover Through Sentinel-2 Multispec...mentioning

confidence: 99%

“…Using multispectral imagery (Fig. 1), winter soil cover rate before spring crops was estimated between one-third and one-half of French fields, with strong spatial variability (Nowak et al 2021). As a comparison, Nitrate Vulnerable Zones cover 68% of the country's agricultural area (Programme d'actions national nitrates 2020).…”

Section: Introductionmentioning

confidence: 99%

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Soil-climate factors have a greater influence on the presence of winter cover crops than regulatory constraints in France

Nowak

Michaud

Marliac

2022

Agron. Sustain. Dev.

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Despite the benefits associated with winter soil cover before sowing a spring crop, this practice is adopted unevenly by farmers. The goal of this paper is to identify and hierarchize the main soil-climate factors that hinder the adoption of cover crops. It is the first study to carry out this analysis at the scale of France, which is a country with a wide variety of soil types and climates. For this country, maps of vegetated winter soil cover prior to the establishment of a spring crop were previously produced for years 2018 and 2019, using Sentinel-2 multispectral images. For approximately half of France's acreage with spring crops, the estimation concerning the presence or absence of a winter cover crop was correlated here with the main soil-climate factors of each field. The inclusion within Nitrate Vulnerable Zones is another potentially important variable to explain cover crop adoption, as regulatory requirements of the Nitrates Directives strongly encourage winter soil cover in these zones to reduce nitrogen losses. Because of the regulatory requirements of the Nitrates Directives regarding winter soil cover, the influence of being located in a Nitrate Vulnerable Zone was also evaluated. But despite these incentives for winter soil cover, inclusion in a Nitrate Vulnerable Zone had little influence on cover crop adoption. Principal component analyses performed for different crop rotations showed that the clay content was the soil-climate factor most negatively correlated with the adoption of cover crops. Cover crops were more frequently established on sandy fields with high organic carbon stocks, which corresponds rather to the characteristics of livestock regions. The development of technical solutions for the establishment and destruction of winter cover crops on clay soils could facilitate the adoption of these crops, and thus improve global water quality.

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Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota

Jain,

John,

Torbick

et al. 2024

Environmental Management

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The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in mitigating climate change, there are very few studies that have assessed the overall spatial distribution of cover crops and tillage practices based on the farm’s pedoclimatic and topographic characteristics. Hence, the primary objective of this study was to use multiple satellite-derived indices and environmental drivers to infer the level of tillage intensity and identify the presence of cover crops in eastern South Dakota (SD). We used a machine learning classifier trained with in situ field samples and environmental drivers acquired from different remote sensing datasets for 2022 and 2023 to map the conservation agriculture practices. Our classification accuracies (>80%) indicate that the employed satellite spectral indices and environmental variables could successfully detect the presence of cover crops and the tillage intensity in the study region. Our analysis revealed that 4% of the corn (Zea mays) and soybean (Glycine max) fields in eastern SD had a cover crop during either the fall of 2022 or the spring of 2023. We also found that environmental factors, specifically seasonal precipitation, growing degree days, and surface texture, significantly impacted the use of conservation practices. The methods developed through this research may provide a viable means for tracking and documenting farmers’ agricultural management techniques. Our study contributes to developing a measurement, reporting, and verification (MRV) solution that could help used to monitor various climate-smart agricultural practices.

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Estimation of winter soil cover by vegetation before spring-sown crops for mainland France using multispectral satellite imagery

Cited by 12 publications

References 32 publications

Dataset about the adoption of winter cover crops at the municipality level for mainland France

Dataset about the adoption of winter cover crops at the municipality level for mainland France

Soil-climate factors have a greater influence on the presence of winter cover crops than regulatory constraints in France

Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota

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