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Potentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo / Yawo Konko in Bois et forêts des tropiques, n° 347 ([02/04/2021])  

Public [article]  inBois et forêts des tropiques > n° 347 [02/04/2021] Titre : Potentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo Type de document : Article/Communication Auteurs : Yawo Konko, Auteur ; Bareremna Afelu, Auteur ; Kouami Kokou, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte de la végétation [Termes IGN] cultures [Termes IGN] dommage [Termes IGN] forêt tropicale [Termes IGN] image Sentinel-MSI [Termes IGN] impact sur l'environnement [Termes IGN] incendie de forêt [Termes IGN] plantation forestière [Termes IGN] savane [Termes IGN] Togo Mots-clés libres : Normalized Burn Ratio Résumé : (auteur) Le réchauffement climatique est un phénomène d’envergure mondiale qui se répercute sur le système climatique. Une des conséquences du réchauffement climatique est l'extension de la période de sécheresse, favorisant ainsi l’augmentation des fréquences du phénomène des feux de végétation. Les feux incontrôlés perturbent l’écologie et la fonctionnalité des écosystèmes, entraînant parfois leur érosion. La présente étude est une contribution pour la gestion des feux de végétation au Togo et porte sur le suivi spatial pour la saison des feux 2018-2019. Elle explore la potentialité des nouvelles données satellitaires Sentinel-2 (S-2) en accès libre dans la gamme de la télédétection optique pour la détection des surfaces brûlées, la cartographie des feux utilitaires et des feux incontrôlés. Elle teste également la performance de la méthode de cartographie des feux de végétation à partir de l’indice NBR (Normalized Burn Ratio) initialement conçue pour les images Landsat et évalue la biomasse végétale brûlée. Les résultats révèlent que les images S-2 présentent du potentiel dans la restitution des surfaces brûlées. La performance de la méthode de l’indice NBR sur les images S-2 est satisfaisante. La cartographie des feux de végétation montre que les feux utilitaires représentent 21,75 % contre 78,25 % pour les feux incontrôlés. L’ensemble des feux de végétation enregistrés a occasionné l’incendie de 5 878 km2 du couvert végétal, soit 10,39 % du territoire national. Le couvert végétal brûlé est composé majoritairement de savanes (33,12 %), de cultures et jachères (24,48 %), de plantations (14,59 %), de forêts claires (14,43 %) et de forêts riveraines (13,02 %). Les résultats obtenus constituent des éléments tangibles pour le suivi, la sensibilisation, l’élaboration des plans d’aménagement, de prévention et de gestion des feux. Numéro de notice : A2021-503 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.19182/bft2021.347.a36349 date de publication en ligne : 31/03/2021 En ligne : https://doi.org/10.19182/bft2021.347.a36349 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98095 [article]

Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie / Andrew Neary in Forest ecology and management, vol 479 ([01/01/2021])  

Public [article]  inForest ecology and management > vol 479 [01/01/2021] . - 12 p. Titre : Topographic, edaphic and climate influences on aspen (Populus tremuloides) drought stress on an intermountain bunchgrass prairie Type de document : Article/Communication Auteurs : Andrew Neary, Auteur ; Ricardo Mata-González, Auteur ; Heidi Schmalz, Auteur Année de publication : 2021 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de sensibilité [Termes IGN] climat [Termes IGN] écophysiologie [Termes IGN] état du sol [Termes IGN] facteur édaphique [Termes IGN] hauteur des arbres [Termes IGN] humidité du sol [Termes IGN] manteau neigeux [Termes IGN] Oregon (Etats-Unis) [Termes IGN] Poaceae [Termes IGN] Populus tremuloides [Termes IGN] prairie [Termes IGN] série temporelle [Termes IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Quaking aspen, Populus tremuloides, has experienced severe declines in recent years in part due to the effects of changing climate and extreme drought. This study set out to investigate these effects by assessing associations of climatic, edaphic and topographic variables with physiological drought stress in aspen. The study took place on the Zumwalt Prairie in northeastern Oregon, a semi-arid bunchgrass prairie where aspen occur in isolated stands associated with riparian areas and late-season persistence of snow drifts. Using a 33-year time series of Landsat imagery to detect associations of aspen stands late-season snow cover and field measurements of soil moisture in aspen stands during 2017, we found while snow dominated stands were associated with greater soil moisture during spring, levels had equilibrated to those of other upland stands by summer. Measurements of predawn and midday stem Ψ in multiple height classes of aspen ramets revealed associations of both shallow soil moisture and vapor pressure deficit with physiological drought stress in aspen. Analysis of soil texture class revealed an important association with midday stem Ψ, with finer textured soils associated with decreased stem Ψ in comparison to coarser textured soils. While neither topographical characteristics nor snow cover were found to be important drivers of drought stress, topographical curvature was found to have a strong influence on summer soil moisture in upland stands. These findings contribute to our understanding of aspen physiology, drought ecology and landscape hydrology toward the xeric margin of aspen’s range. This information can help land managers anticipate and adapt to changing climates and understand their effects on key plant species such as aspen. Numéro de notice : A2021-001 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118530 date de publication en ligne : 08/09/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96028 [article]

Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data / Yaotong Cai in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 92 (October 2020) . - n° 102164 Titre : Mapping wetland using the object-based stacked generalization method based on multi-temporal optical and SAR data Type de document : Article/Communication Auteurs : Yaotong Cai, Auteur ; Xinyu Li, Auteur ; Meng Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102164 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] algorithme de généralisation [Termes IGN] analyse d'image orientée objet [Termes IGN] cartographie thématique [Termes IGN] Chine [Termes IGN] filtre de déchatoiement [Termes IGN] image radar moirée [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] modélisation spatio-temporelle [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] prairie [Termes IGN] rétrodiffusion [Termes IGN] série temporelle [Termes IGN] zone humide Résumé : (auteur) Wetland ecosystems have experienced dramatic challenges in the past few decades due to natural and human factors. Wetland maps are essential for the conservation and management of terrestrial ecosystems. This study is to obtain an accurate wetland map using an object-based stacked generalization (Stacking) method on the basis of multi-temporal Sentinel-1 and Sentinel-2 data. Firstly, the Robust Adaptive Spatial Temporal Fusion Model (RASTFM) is used to get time series Sentinel-2 NDVI, from which the vegetation phenology variables are derived by the threshold method. Subsequently, both vertical transmit-vertical receive (VV) and vertical transmit-horizontal receive (VH) polarization backscatters (σ0 VV, σ0 VH) are obtained using the time series Sentinel-1 images. Speckle noise inherent in SAR data, resulting in over-segmentation or under-segmentation, can affect image segmentation and degrade the accuracies of wetland classification. Therefore, we segment Sentinel-2 multispectral images to delineate meaningful objects in this study. Then, in order to reduce data redundancy and computation time, we analyze the optimal feature combination using the Sentinel-2 multispectral images, Sentinel-2 NDVI time series, phenological variables and other vegetation index derived from Sentinel-2 multispectral images, as well as time series Sentinel-1 backscatters at the object level. Finally, the stacked generalization algorithm is utilized to extract the wetland information based on the optimal feature combination in the Dongting Lake wetland. The overall accuracy and Kappa coefficient of the object-based stacked generalization method are 92.46% and 0.92, which are 3.88% and 0.04 higher than that using the pixel-based method. Moreover, the object-based stacked generalization algorithm is superior to single classifiers in classifying vegetation of high heterogeneity areas. Numéro de notice : A2020-748 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102164 date de publication en ligne : 07/06/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102164 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96398 [article]

Temporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 4 (April 2020) . - pp 225 - 233 Titre : Temporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau Type de document : Article/Communication Auteurs : Gaofei Yin, Auteur ; Ainong Li, Auteur ; Zhengjian Zhang, Auteur ; Guangbin Lei, Auteur Année de publication : 2020 Article en page(s) : pp 225 - 233 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] corrélation d'images [Termes IGN] image Aqua-MODIS [Termes IGN] image Terra-MODIS [Termes IGN] Leaf Area Index [Termes IGN] plateau [Termes IGN] prairie [Termes IGN] série temporelle [Termes IGN] température au sol [Termes IGN] Tibet Résumé : (Auteur) Time series of leaf area index (LAI) products are now widely used, and the temporal validation is the prerequisite for their proper application. However, a systematical comparison between different products using both direct and indirect methods is still lacking. The objective of this paper is to assess and compare the temporal performances of four LAI products: Moderate Resolution Imaging Spectroradiometer (MODIS) LAI (MOD)15A2, MOD15A2h, Geoland2 Version 1 (GEOV1), and Global Land Surface Satellite (GLASS). The study area, which is dominated by grasslands, is located in the northeastern Tibetan Plateau (TP), and temperature is the main stress factor affecting grass growth. Both a correlation analysis with temperature and a direct comparison with temporally continuous LAI reference maps were implemented in our temporal validation experiments. The results show that no single product can capture the rapid change and the seasonal trend in LAI simultaneously, and the compositing period used in each product determines the quality of the corresponding LAI time series. The MOD15A2 and MOD15A2h products, which have short compositing windows (eight days), are suitable for detecting rapid change. A grazing-induced biomass decrease that occurred around day of year 205 in 2014 in our study area was clearly revealed in these two products. For the GEOV1 and GLASS products, which have compositing windows of 30 days and 1 year, respectively, the grazing date was shifted (GEOV1) or even invisible (GLASS). However, products with prolonged compositing windows may be more robust to observation noise, and the resulting products may be suitable for capturing the seasonal trend. This study highlights that the concurrent use of data from various sensors onboard different satellites, and the introduction of new generations of satellites (e.g., Gaofen-6), are two promising ways to further improve existing LAI time series. Numéro de notice : A2020-129 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.4.225 date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.14358/PERS.86.4.225 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94804 [article]

Prediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series / Mathieu Fauvel in Remote sensing of environment, Vol 237 (February 2020)  

Public [article]  inRemote sensing of environment > Vol 237 (February 2020) . - 13 p. Titre : Prediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series Type de document : Article/Communication Auteurs : Mathieu Fauvel, Auteur ; Maylis Lopes, Auteur ; Titouan Dubo, Auteur ; Justine Rivers-Moore, Auteur ; Pierre-Louis Frison , Auteur ; Nicolas Gross, Auteur ; Annie Ouin, Auteur Année de publication : 2020 Projets : SEBIOREF / Ouin, Annie Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] biodiversité végétale [Termes IGN] classification par forêts aléatoires [Termes IGN] Haute-Garonne (31) [Termes IGN] image radar moirée [Termes IGN] image RapidEye [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de diversité [Termes IGN] indice de végétation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] prairie [Termes IGN] série temporelle [Termes IGN] taxinomie Résumé : (auteur) The prediction of grasslands plant diversity using satellite image time series is considered in this article. Fifteen months of freely available Sentinel optical and radar data were used to predict taxonomic and functional diversity at the pixel scale (10 m × 10 m) over a large geographical extent (40,000 km2). 415 field measurements were collected in 83 grasslands to train and validate several statistical learning methods. The objective was to link the satellite spectro-temporal data to the plant diversity indices. Among the several diversity indices tested, Simpson and Shannon indices were best predicted with a coefficient of determination around 0.4 using a Random Forest predictor and Sentinel-2 data. The use of Sentinel-1 data was not found to improve significantly the prediction accuracy. Using the Random Forest algorithm and the Sentinel-2 time series, the prediction of the Simpson index was performed. The resulting map highlights the intra-parcel variability and demonstrates the capacity of satellite image time series to monitor grasslands plant taxonomic diversity from an ecological viewpoint. Numéro de notice : A2020-004 Affiliation des auteurs : UPEM-LaSTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2019.111536 date de publication en ligne : 26/11/2019 En ligne : https://doi.org/10.1016/j.rse.2019.111536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94296 [article]

On the joint exploitation of optical and SAR satellite imagery for grassland monitoring / Anatol Garioud (2020)  

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Change detection work-flow for mapping changes from arable lands to permanent grasslands with advanced boosting methods / Jiří Šandera in Geodetski vestnik, vol 63 n° 3 (September - November 2019)  

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Land-cover change in the Wulagai grassland, Inner Mongolia of China between 1986 and 2014 analysed using multi-temporal Landsat images / Temulun Tangud in Geocarto international, vol 34 n° 11 ([15/08/2019])  

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Evaluating the potential of the red edge channel for C3 (Festuca spp.) grass discrimination using Sentinel-2 and Rapid Eye satellite image data / Charles Otunga in Geocarto international, vol 34 n° 10 ([15/07/2019])  

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A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

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Challenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (2019)  

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Joint analysis of SAR and optical satellite images time series for grassland event detection / Anatol Garioud (2019)

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Microwave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)  

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Soil moisture assessment in grasslands using optical remote sensing data / Luc Beraud (2019) 

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Estimating forest standing biomass in savanna woodlands as an indicator of forest productivity using the new generation WorldView-2 sensor / Timothy Dube in Geocarto international, vol 33 n° 2 (February 2018)  

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