Dry season forage assessment across senegalese rangelands using earth observation data
Strengthening of feed security in the Sahel is urgently needed given the climate change and growing human population. A prerequisite to this is sustainable use of rangeland forage resources for livestock. Many studies have focused on the assessment of rangeland resources during the rainy season, whi...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2022.931299/full |
| _version_ | 1811208261549948928 |
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| author | Adama Lo Adama Lo Abdoul Aziz Diouf Ibrahima Diedhiou Cyrille Djitamagne Edouard Bassène Cyrille Djitamagne Edouard Bassène Louise Leroux Louise Leroux Torbern Tagesson Torbern Tagesson Rasmus Fensholt Pierre Hiernaux Anne Mottet Simon Taugourdeau Simon Taugourdeau Daouda Ngom Ibra Touré Babacar Ndao Mamadou Adama Sarr Mamadou Adama Sarr |
| author_facet | Adama Lo Adama Lo Abdoul Aziz Diouf Ibrahima Diedhiou Cyrille Djitamagne Edouard Bassène Cyrille Djitamagne Edouard Bassène Louise Leroux Louise Leroux Torbern Tagesson Torbern Tagesson Rasmus Fensholt Pierre Hiernaux Anne Mottet Simon Taugourdeau Simon Taugourdeau Daouda Ngom Ibra Touré Babacar Ndao Mamadou Adama Sarr Mamadou Adama Sarr |
| author_sort | Adama Lo |
| collection | DOAJ |
| description | Strengthening of feed security in the Sahel is urgently needed given the climate change and growing human population. A prerequisite to this is sustainable use of rangeland forage resources for livestock. Many studies have focused on the assessment of rangeland resources during the rainy season, while only a few have focused on the dry season which is the longest and most demanding period for livestock in Sahelian rangelands. The objective of this study is to develop remote sensing-based models for estimating dry season forage vegetation mass. To that end, 29 vegetation indices calculated from each of the MODIS-MCD43A4 (500 m), Landsat-8 (30 m), and Sentinel-2 (10 m) satellite products were used and tested against in situ data collected during three field-measurement campaigns in 2021 at eleven monitoring sites across Senegalese rangelands. Four statistical models were tested, namely, random forest, gradient boosting machines, and simple linear and multiple linear regressions. The two main vegetation mass variables modeled from remote sensing imagery were the standing herbaceous and litter dry mass (BH) and total forage dry mass (BT) with a dry mass of woody plant leaves added to BH. Overall, Sentinel-2 data provided the best performance for the assessment of BH with multiple linear regression (R2 = 0.74; RMSE = 378 kg DM/ha) using NDI5 (Normalized Difference Index5), GRCI (Green Residue Cover Index), SRI (Simple Ratio Index), TCARI (Transformed Chlorophyll Absorption in Reflectance Index), and DFI (Dead Fuel Index) indices. For BT, the best model was also obtained from Sentinel-2 data, including RVI3 (Ratio Vegetation Index3) (R2 = 0.78; RMSE = 496 kg DM/ha). Results showed the suitability of combining the red, green, blue, NIR, SWIR1, and SWIR2 bands in monitoring forage availability during the dry season. Our study revealed that the spectral richness of the optical sensor systems Sentinel-2, Landsat-8, and MODIS-MCD43A4 allowed for accurate assessments of dry-season forage mass of semi-arid rangelands. Adding to this, the high spatial and temporal resolution of Sentinel-2 satellite imagery makes this a promising data source for timely monitoring. These findings can support the monitoring of the animal feed balance in Sahelian countries and contribute to enhancing the resilience of pastoralism toward feed shortage through early warning systems. |
| first_indexed | 2024-04-12T04:18:50Z |
| format | Article |
| id | doaj.art-60a955dbe5544c08b9eedd43492b27d6 |
| institution | Directory Open Access Journal |
| issn | 2296-665X |
| language | English |
| last_indexed | 2024-04-12T04:18:50Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Environmental Science |
| spelling | doaj.art-60a955dbe5544c08b9eedd43492b27d62022-12-22T03:48:19ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2022-09-011010.3389/fenvs.2022.931299931299Dry season forage assessment across senegalese rangelands using earth observation dataAdama Lo0Adama Lo1Abdoul Aziz Diouf2Ibrahima Diedhiou3Cyrille Djitamagne Edouard Bassène4Cyrille Djitamagne Edouard Bassène5Louise Leroux6Louise Leroux7Torbern Tagesson8Torbern Tagesson9Rasmus Fensholt10Pierre Hiernaux11Anne Mottet12Simon Taugourdeau13Simon Taugourdeau14Daouda Ngom15Ibra Touré16Babacar Ndao17Mamadou Adama Sarr18Mamadou Adama Sarr19Centre de Suivi Ecologique, Dakar, SénégalENSA, Université Iba Der Thiam de Thiès, Thiès, SénégalCentre de Suivi Ecologique, Dakar, SénégalENSA, Université Iba Der Thiam de Thiès, Thiès, SénégalCentre de Suivi Ecologique, Dakar, SénégalUCAD, Département de Biologie Végétale, Dakar, SénégalCIRAD, UPR AIDA, Dakar, SénégalAIDA, Univ Montpellier, CIRAD, Montpellier, FranceDepartment of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen, Copenhagen, DenmarkDepartment of Physical Geography and Ecosystem Sciences, Lund University, Lund, SwedenDepartment of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen, Copenhagen, DenmarkPastoralisme Conseil, Caylus, FranceFood and Agriculture Organization of the United Nations, Animal Production and Health Division, Rome, Italy0CIRAD, UMR SELMET-PPZS, Dakar, Sénégal1UMR SELMET, Univ Montpellier CIRAD INRAE Institut AGRO, Montpellier, FranceUCAD, Département de Biologie Végétale, Dakar, Sénégal0CIRAD, UMR SELMET-PPZS, Dakar, SénégalCentre de Suivi Ecologique, Dakar, SénégalCentre de Suivi Ecologique, Dakar, Sénégal2Section de Géographie, UFR Lettres et Sciences Humaines, Université Gaston Berger (UGB), Saint-Louis, SénégalStrengthening of feed security in the Sahel is urgently needed given the climate change and growing human population. A prerequisite to this is sustainable use of rangeland forage resources for livestock. Many studies have focused on the assessment of rangeland resources during the rainy season, while only a few have focused on the dry season which is the longest and most demanding period for livestock in Sahelian rangelands. The objective of this study is to develop remote sensing-based models for estimating dry season forage vegetation mass. To that end, 29 vegetation indices calculated from each of the MODIS-MCD43A4 (500 m), Landsat-8 (30 m), and Sentinel-2 (10 m) satellite products were used and tested against in situ data collected during three field-measurement campaigns in 2021 at eleven monitoring sites across Senegalese rangelands. Four statistical models were tested, namely, random forest, gradient boosting machines, and simple linear and multiple linear regressions. The two main vegetation mass variables modeled from remote sensing imagery were the standing herbaceous and litter dry mass (BH) and total forage dry mass (BT) with a dry mass of woody plant leaves added to BH. Overall, Sentinel-2 data provided the best performance for the assessment of BH with multiple linear regression (R2 = 0.74; RMSE = 378 kg DM/ha) using NDI5 (Normalized Difference Index5), GRCI (Green Residue Cover Index), SRI (Simple Ratio Index), TCARI (Transformed Chlorophyll Absorption in Reflectance Index), and DFI (Dead Fuel Index) indices. For BT, the best model was also obtained from Sentinel-2 data, including RVI3 (Ratio Vegetation Index3) (R2 = 0.78; RMSE = 496 kg DM/ha). Results showed the suitability of combining the red, green, blue, NIR, SWIR1, and SWIR2 bands in monitoring forage availability during the dry season. Our study revealed that the spectral richness of the optical sensor systems Sentinel-2, Landsat-8, and MODIS-MCD43A4 allowed for accurate assessments of dry-season forage mass of semi-arid rangelands. Adding to this, the high spatial and temporal resolution of Sentinel-2 satellite imagery makes this a promising data source for timely monitoring. These findings can support the monitoring of the animal feed balance in Sahelian countries and contribute to enhancing the resilience of pastoralism toward feed shortage through early warning systems.https://www.frontiersin.org/articles/10.3389/fenvs.2022.931299/fullforage dry massdry seasonMODIS MCD43A4Landsat-8Sentinel-2food security |
| spellingShingle | Adama Lo Adama Lo Abdoul Aziz Diouf Ibrahima Diedhiou Cyrille Djitamagne Edouard Bassène Cyrille Djitamagne Edouard Bassène Louise Leroux Louise Leroux Torbern Tagesson Torbern Tagesson Rasmus Fensholt Pierre Hiernaux Anne Mottet Simon Taugourdeau Simon Taugourdeau Daouda Ngom Ibra Touré Babacar Ndao Mamadou Adama Sarr Mamadou Adama Sarr Dry season forage assessment across senegalese rangelands using earth observation data Frontiers in Environmental Science forage dry mass dry season MODIS MCD43A4 Landsat-8 Sentinel-2 food security |
| title | Dry season forage assessment across senegalese rangelands using earth observation data |
| title_full | Dry season forage assessment across senegalese rangelands using earth observation data |
| title_fullStr | Dry season forage assessment across senegalese rangelands using earth observation data |
| title_full_unstemmed | Dry season forage assessment across senegalese rangelands using earth observation data |
| title_short | Dry season forage assessment across senegalese rangelands using earth observation data |
| title_sort | dry season forage assessment across senegalese rangelands using earth observation data |
| topic | forage dry mass dry season MODIS MCD43A4 Landsat-8 Sentinel-2 food security |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2022.931299/full |
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