Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize
The annual certification of organic agriculture products includes an in situ inspection of the fields declared organic. This inspection is more difficult, time-consuming, and costly for large farms or in production regions located in remote areas. The global objective of this research is to assess h...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/1/117 |
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| author | Antoine Denis Baudouin Desclee Silke Migdall Herbert Hansen Heike Bach Pierre Ott Amani Louis Kouadio Bernard Tychon |
| author_facet | Antoine Denis Baudouin Desclee Silke Migdall Herbert Hansen Heike Bach Pierre Ott Amani Louis Kouadio Bernard Tychon |
| author_sort | Antoine Denis |
| collection | DOAJ |
| description | The annual certification of organic agriculture products includes an in situ inspection of the fields declared organic. This inspection is more difficult, time-consuming, and costly for large farms or in production regions located in remote areas. The global objective of this research is to assess how spatial remote sensing may support the organic crop certification process by developing a method that would enable certification bodies to target for priority in situ control crop fields declared as organic but that would show on satellite imagery an appearance closer to conventional fields. For this purpose, the ability of multispectral satellite images to discriminate between organic and conventional maize fields was assessed through the use of a set of four satellite images of different spatial and spectral resolutions acquired at different crop growth stages over a large number of maize fields (32) that are part of an operational farm in Germany. In support of this main objective, a set of in situ measurements (leaf hyperspectral reflectance, chlorophyll, and nitrogen content and dry matter percentage, crop canopy cover, height, wet biomass and dry matter percentage, soil chemical composition) was conducted to characterize the nature of the biochemical and biophysical differences between organic and conventional maize fields. The results of this research showed that highly significant biochemical and biophysical differences between a large number of organic and conventional maize fields may exist at identified crop growth stages and that these differences may be sufficiently pronounced to enable the complete discrimination between crop management modes using satellite images issued from quite common multispectral satellite sensors through the use of spectral or spatial heterogeneity indices. These results are very encouraging and suggest, for the first time, that satellite images could effectively support the organic maize certification process. |
| first_indexed | 2024-03-10T13:35:37Z |
| format | Article |
| id | doaj.art-3802d16f47d5480ba64cfaaee6feb9de |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T13:35:37Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3802d16f47d5480ba64cfaaee6feb9de2023-11-21T07:33:43ZengMDPI AGRemote Sensing2072-42922020-12-0113111710.3390/rs13010117Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional MaizeAntoine Denis0Baudouin Desclee1Silke Migdall2Herbert Hansen3Heike Bach4Pierre Ott5Amani Louis Kouadio6Bernard Tychon7Water, Environment and Development Unit, Environmental Sciences and Management Department, Arlon Campus Environment, UR SPHERES, University of Liège, 185 Avenue de Longwy, 6700 Arlon, BelgiumKEYOBS SA, CAP Business Center, 31 Rue d’Abhooz, 4040 Herstal, BelgiumVISTA GmbH, Gabelsbergerstraße 51, D-80333 München, GermanyKEYOBS SA, CAP Business Center, 31 Rue d’Abhooz, 4040 Herstal, BelgiumVISTA GmbH, Gabelsbergerstraße 51, D-80333 München, GermanyECOCERT SA, BP 47, Lieu dit Lamothe, 32600 L’Isle Jourdain, FranceWater, Environment and Development Unit, Environmental Sciences and Management Department, Arlon Campus Environment, UR SPHERES, University of Liège, 185 Avenue de Longwy, 6700 Arlon, BelgiumWater, Environment and Development Unit, Environmental Sciences and Management Department, Arlon Campus Environment, UR SPHERES, University of Liège, 185 Avenue de Longwy, 6700 Arlon, BelgiumThe annual certification of organic agriculture products includes an in situ inspection of the fields declared organic. This inspection is more difficult, time-consuming, and costly for large farms or in production regions located in remote areas. The global objective of this research is to assess how spatial remote sensing may support the organic crop certification process by developing a method that would enable certification bodies to target for priority in situ control crop fields declared as organic but that would show on satellite imagery an appearance closer to conventional fields. For this purpose, the ability of multispectral satellite images to discriminate between organic and conventional maize fields was assessed through the use of a set of four satellite images of different spatial and spectral resolutions acquired at different crop growth stages over a large number of maize fields (32) that are part of an operational farm in Germany. In support of this main objective, a set of in situ measurements (leaf hyperspectral reflectance, chlorophyll, and nitrogen content and dry matter percentage, crop canopy cover, height, wet biomass and dry matter percentage, soil chemical composition) was conducted to characterize the nature of the biochemical and biophysical differences between organic and conventional maize fields. The results of this research showed that highly significant biochemical and biophysical differences between a large number of organic and conventional maize fields may exist at identified crop growth stages and that these differences may be sufficiently pronounced to enable the complete discrimination between crop management modes using satellite images issued from quite common multispectral satellite sensors through the use of spectral or spatial heterogeneity indices. These results are very encouraging and suggest, for the first time, that satellite images could effectively support the organic maize certification process.https://www.mdpi.com/2072-4292/13/1/117spatial remote sensingmultispectral satellite imageorganic crop certificationorganic agricultureconventional agriculturemaize |
| spellingShingle | Antoine Denis Baudouin Desclee Silke Migdall Herbert Hansen Heike Bach Pierre Ott Amani Louis Kouadio Bernard Tychon Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize Remote Sensing spatial remote sensing multispectral satellite image organic crop certification organic agriculture conventional agriculture maize |
| title | Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize |
| title_full | Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize |
| title_fullStr | Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize |
| title_full_unstemmed | Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize |
| title_short | Multispectral Remote Sensing as a Tool to Support Organic Crop Certification: Assessment of the Discrimination Level between Organic and Conventional Maize |
| title_sort | multispectral remote sensing as a tool to support organic crop certification assessment of the discrimination level between organic and conventional maize |
| topic | spatial remote sensing multispectral satellite image organic crop certification organic agriculture conventional agriculture maize |
| url | https://www.mdpi.com/2072-4292/13/1/117 |
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