Détail de l'auteur
Auteur Stéphane Mermoz |
Documents disponibles écrits par cet auteur (3)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesNear-real-time identification of the drivers of deforestation in French Guiana / Marie Ballère (2021)
Titre : Near-real-time identification of the drivers of deforestation in French Guiana Type de document : Article/Communication Auteurs : Marie Ballère Editeur : Munich [Allemagne] : European Geosciences Union EGU Année de publication : 2021 Conférence : EGU 2021, General Assembly 19/04/2021 30/04/2021 en ligne OA Abstracts only Format : 21 x 30 cm Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] déboisement
[Termes IGN] exploitation forestière
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] mine d'or
[Termes IGN] surveillance forestière
[Termes IGN] urbanisationNuméro de notice : C2021-004 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans En ligne : https://doi.org/10.5194/egusphere-egu21-16015 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97598
Titre : SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery Type de document : Article/Communication Auteurs : Marie Ballère Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 112159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] surveillance forestière
[Termes IGN] temps réelRésumé : (auteur) French Guiana forests cover 8 million hectares. With 98% of emerged land covered by forests, French Guiana is the area with the highest proportion of forest cover in the world. These forests are home to an exceptionally rich and diverse wealth of biodiversity that is both vulnerable and under threat due to high levels of pressure from human activity. As part of the French territory, French Guiana benefits from determined and continuous national efforts in the preservation of biodiversity and the environmental functionalities of ecosystems. The loss and fragmentation of forest cover caused by gold mining (legal and illegal), smallholder agriculture and forest exploitation, are considered as small-scale disturbances, although representing strong effects to vulnerable natural habitats, landscapes, and local populations. To monitor forest management programs and combat illegal deforestation and forest opening near-real time alerts system based on remote sensing data are required. For this large territory under frequent cloud cover, Synthetic-Aperture Radar (SAR) data appear to be the best adapted. In this paper, a method for forest alerts in a near-real time context based on Sentinel-1 data over the whole of French Guiana (83,534 km2) was developed and evaluated. The assessment was conducted for 2 years between 2016 and 2018 and includes comparisons with reference data provided by French Guiana forest organizations and comparisons with the existing University of Maryland Global Land Analysis and Discovery Forest Alerts datasets based on Landsat data. The reference datasets include 1,867 plots covering 2,124.5 ha of gold mining, smallholder agriculture and forest exploitation. The validation results showed high user accuracies (96.2%) and producer accuracies (81.5%) for forest loss detection, with the latter much higher than for optical forest alerts (36.4%). The forest alerts maps were also compared in terms of detection timing, showing systematic temporal delays of up to one year in the optical method compared to the SAR method. These results highlight the benefits of SAR over optical imagery for forest alerts detection in French Guiana. Finally, the potential of the SAR method applied to tropical forests is discussed. The SAR-based map of this study is available on http://cesbiomass.net/. Numéro de notice : A2021-066 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2020.112159 Date de publication en ligne : 05/11/2020 En ligne : https://doi.org/10.1016/j.rse.2020.112159 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96937
in Remote sensing of environment > Vol 252 (January 2021) . - n° 112159[article]
Titre : Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications Type de document : Article/Communication Auteurs : Amanda Veloso, Auteur ; Stéphane Mermoz, Auteur ; Alexandre Bouvet, Auteur ; Thuy Le Toan, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 415 - 426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] blé (céréale)
[Termes IGN] cultures
[Termes IGN] Glycine max
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] maïs (céréale)
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance agricole
[Termes IGN] tournesol
[Termes IGN] variation saisonnière
[Termes IGN] variation temporelleRésumé : (auteur) Crop monitoring information is essential for food security and to improve our understanding of the role of agriculture on climate change, among others. Remotely sensing optical and radar data can help to map crop types and to estimate biophysical parameters, especially with the availability of an unprecedented amount of free Sentinel data within the Copernicus programme. These datasets, whose continuity is guaranteed up to decades, offer a unique opportunity to monitor crops systematically every 5 to 10 days. Before developing operational monitoring methods, it is important to understand the temporal variations of the remote sensing signal of different crop types in a given region. In this study, we analyse the temporal trajectory of remote sensing data for a variety of winter and summer crops that are widely cultivated in the world (wheat, rapeseed, maize, soybean and sunflower). The test region is in southwest France, where Sentinel-1 data have been acquired since 2014. Because Sentinel-2 data were not available for this study, optical satellites similar to Sentinel-2 are used, mainly to derive NDVI, for a comparison between the temporal behaviors with radar data. The SAR backscatter and NDVI temporal profiles of fields with varied management practices and environmental conditions are interpreted physically. Key findings from this analysis, leading to possible applications of Sentinel-1 data, with or without the conjunction of Sentinel-2, are then described. This study points out the interest of SAR data and particularly the VH/VV ratio, which is poorly documented in previous studies. Numéro de notice : A2017-418 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.07.015 En ligne : https://doi.org/10.1016/j.rse.2017.07.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86311
in Remote sensing of environment > vol 199 (15 September 2017) . - pp 415 - 426[article]
