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Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery / Zifeng Wang in Remote sensing of environment, Vol 255 (March 2021)  

Public [article]  inRemote sensing of environment > Vol 255 (March 2021) . - n° 112281 Titre : Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery Type de document : Article/Communication Auteurs : Zifeng Wang, Auteur ; Junguo Liu, Auteur ; Jinbao Li, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Asie du sud-est [Termes IGN] bassin hydrographique [Termes IGN] données hydrographiques [Termes IGN] données topographiques [Termes IGN] extraction de traits caractéristiques [Termes IGN] image Sentinel-MSI [Termes IGN] modèle numérique de surface [Termes IGN] réseau de drainage [Termes IGN] réseau fluvial Résumé : (auteur) Extraction of drainage networks is an important element of river flow routing in hydrology and large-scale estimates of river behaviors in Earth sciences. Emerging studies with a focus on greenhouse gases reveal that small rivers can contribute to more than half of the global carbon emissions from inland waters (including lakes and wetlands). However, large-scale extraction of drainage networks is constrained by the coarse resolution of observational data and models, which hinders assessments of terrestrial hydrological and biogeochemical cycles. Recognizing that Sentinel-2 satellite can detect surface water up to a 10-m resolution over large scales, we propose a new method named Remote Sensing Stream Burning (RSSB) to integrate high-resolution observational flow location with coarse topography to improve the extraction of drainage network. In RSSB, satellite-derived input is integrated in a spatially continuous manner, producing a quasi-bathymetry map where relative relief is enforced, enabling a fine-grained, accurate, and multitemporal extraction of drainage network. RSSB was applied to the Lancang-Mekong River basin to derive a 10-m resolution drainage network, with a significant reduction in location errors as validated by the river centerline measurements. The high-resolution extraction resulted in a realistic representation of meanders and detailed network connections. Further, RSSB enabled a multitemporal extraction of river networks during wet/dry seasons and before/after the formation of new channels. The proposed method is fully automated, meaning that the network extraction preserves basin-wide connectivity without requiring any postprocessing, hence facilitating the construction of drainage networks data with openly accessible imagery. The RSSB method provides a basis for the accurate representation of drainage networks that maintains channel connectivity, allows a more realistic inclusion of small rivers and streams, and enables a greater understanding of complex but active exchange between inland water and other related Earth system components. Numéro de notice : A2021-191 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112281 date de publication en ligne : 21/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112281 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97112 [article]

Optimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam / Vu Anh Tuan in European journal of remote sensing, vol 54 n° 1 (2021)  

Public [article]  inEuropean journal of remote sensing > vol 54 n° 1 (2021) . - pp 13 - 28 Titre : Optimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam Type de document : Article/Communication Auteurs : Vu Anh Tuan, Auteur ; Nguyen Hong Quang, Auteur ; le Thi Thu Hang, Auteur Année de publication : 2021 Article en page(s) : pp 13 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] bande L [Termes IGN] cartographie des risques [Termes IGN] crue [Termes IGN] image ALOS [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] inondation [Termes IGN] Mekong (fleuve) [Termes IGN] optimisation spatiale [Termes IGN] surveillance hydrologique [Termes IGN] Viet Nam Résumé : (auteur) One major characteristic of floods is flood extent. Information on this characteristic is indispensable for flood monitoring. Recently, synthetic aperture radar (SAR) data have been increasing in quality and quantity. This allows more flood studies conducted over large areas regardless of cloud and weather conditions and provides advantages including clear surface water classification based on SAR scattering mechanisms for low values (open water) and high values (inundated vegetation, etc.). However, challenges remain due to sources of uncertainties, such as atmospheric disturbances and vegetation masking parts of water surfaces. Therefore, in this study, we aim to optimize flood mapping processes on flooded vegetation that generated high-value pixels based on a SAR scattering mechanism called double bounce that classifies vegetative flooded water in L-band SAR images. This optimization is nearly impossible using Sentinel-1 scenes. Backscattering of time-series Sentinel-1 and ALOS-2 images acquired for the 2018 and 2019 flood season was analysed, thresholded and hybridized for flood mapping of a study site in the Tam Nong district of the Dong Thap Province of Vietnam. We found that the accuracy of SAR flood maps was improved compared to ground truth data when the SAR-extracted vegetative-flooded plains were considered flooded. Numéro de notice : A2021-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/22797254.2020.1859340 date de publication en ligne : 30/12/2020 En ligne : https://doi.org/10.1080/22797254.2020.1859340 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97015 [article]

Wide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October 2020)  

Public [article]  inRemote sensing > vol 12 n° 19 (October 2020) . - 32 p. Titre : Wide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 Type de document : Article/Communication Auteurs : Dirk Hoekman, Auteur ; Boris Kooij, Auteur ; Marcela J. Quiñones, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 32 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Amazonie [Termes IGN] Bornéo, île de [Termes IGN] déboisement [Termes IGN] dégradation de l'environnement [Termes IGN] détection de changement [Termes IGN] forêt tropicale [Termes IGN] image radar [Termes IGN] image Sentinel-SAR [Termes IGN] image TerraSAR-X [Termes IGN] modèle physique [Termes IGN] série temporelle [Termes IGN] surveillance forestière [Termes IGN] tourbière Résumé : (auteur) The use of Sentinel-1 (S1) radar for wide-area, near-real-time (NRT) tropical-forest-change monitoring is discussed, with particular attention to forest degradation and deforestation. Since forest change can relate to processes ranging from high-impact, large-scale conversion to low-impact, selective logging, and can occur in sites having variable topographic and environmental properties such as mountain slopes and wetlands, a single approach is insufficient. The system introduced here combines time-series analysis of small objects identified in S1 data, i.e., segments containing linear features and apparent small-scale disturbances. A physical model is introduced for quantifying the size of small (upper-) canopy gaps. Deforestation detection was evaluated for several forest landscapes in the Amazon and Borneo. Using the default system settings, the false alarm rate (FAR) is very low (less than 1%), and the missed detection rate (MDR) varies between 1.9% ± 1.1% and 18.6% ± 1.0% (90% confidence level). For peatland landscapes, short radar detection delays up to several weeks due to high levels of soil moisture may occur, while, in comparison, for optical systems, detection delays up to 10 months were found due to cloud cover. In peat swamp forests, narrow linear canopy gaps (road and canal systems) could be detected with an overall accuracy of 85.5%, including many gaps barely visible on hi-res SPOT-6/7 images, which were used for validation. Compared to optical data, subtle degradation signals are easier to detect and are not quickly lost over time due to fast re-vegetation. Although it is possible to estimate an effective forest-cover loss, for example, due to selective logging, and results are spatiotemporally consistent with Sentinel-2 and TerraSAR-X reference data, quantitative validation without extensive field data and/or large hi-res radar datasets, such as TerraSAR-X, remains a challenge. Numéro de notice : A2020-633 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs12193263 date de publication en ligne : 08/10/2020 En ligne : https://doi.org/10.3390/rs12193263 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96056 [article]

Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping / Alvin B. Baloloy in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 95 - 117 Titre : Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping Type de document : Article/Communication Auteurs : Alvin B. Baloloy, Auteur ; Ariel C. Blanco, Auteur ; Raymund Rhommel StaAna, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 95 - 117 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spectrale [Termes IGN] Asie du sud-est [Termes IGN] carte de la végétation [Termes IGN] espèce exotique envahissante [Termes IGN] image captée par drone [Termes IGN] image Landsat-8 [Termes IGN] image proche infrarouge [Termes IGN] image Sentinel-MSI [Termes IGN] indice de végétation [Termes IGN] mangrove [Termes IGN] orthophotographie [Termes IGN] Philippines [Termes IGN] Short Waves InfraRed [Termes IGN] surveillance du littoral Résumé : (auteur) Numéro de notice : A2020-354 Affiliation des auteurs : non IGN Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.06.001 date de publication en ligne : 11/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.06.001 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95240 [article]

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Incorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping / Kristofer Lasko in Geocarto international, vol 35 n° 6 ([01/05/2020])  

Public [article]  inGeocarto international > vol 35 n° 6 [01/05/2020] Titre : Incorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping Type de document : Article/Communication Auteurs : Kristofer Lasko, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Asie du sud-est [Termes IGN] bande C [Termes IGN] carte de la végétation [Termes IGN] cartographie des risques [Termes IGN] dynamique de la végétation [Termes IGN] image Aqua-MODIS [Termes IGN] image multibande [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] image Terra-MODIS [Termes IGN] incendie de forêt [Termes IGN] incertitude temporelle [Termes IGN] Laos [Termes IGN] qualité de l'air [Termes IGN] Thaïlande [Termes IGN] zone sinistrée Résumé : (auteur) Wildland fires result in a unique signal detectable by multispectral remote sensing and synthetic aperture radar (SAR). However, in many regions, such as Southeast Asia, persistent cloud cover and aerosols temporarily obstruct multispectral satellite observations of burned area, including the MODIS MCD64A1 Burned Area Product (BAP). Multiple days between cloud free pre- and post-burn MODIS observations result in burn date uncertainty. We incorporate cloud-penetrating, C-band SAR-with the MODIS MCD64A1 BAP in Southeast Asia, to exploit the strengths of each dataset to better estimate the burn date and reduce the potential burn date uncertainty range. We incorporate built-in quality control using MCD64A1 to reduce erroneous pixel updating. We test the method over part of Laos and Thailand during April 2016 and found average uncertainty reduction of 4.5 d, improving 15% of MCD64A1 pixels. A new BAP could improve monitoring temporal trends of wildland fires, air quality studies and monitoring post-fire vegetation dynamics. Numéro de notice : A2020-226 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1608592 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/https://doi.org/10.1080/10106049.2019.1608592 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94948 [article]

Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data / Sitinor Atikah Nordin in Geocarto international, vol 34 n° 11 ([15/08/2019])  

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Satellite remote sensing of the variability of the continental hydrology cycle in the lower Mekong basin over the last two decades / Binh Pham-Duc (2018)  

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Monitoring surface urban heat island formation in a tropical mountain city using Landsat data (1987–2015) / Ronald C. Estoque in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)  

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Remote sensing of forest degradation in Southeast Asia—Aiming for a regional view through 5–30 m satellite data / Jukka Miettinen in Global ecology and conservation, vol 2 (December 2014)  

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La certification / Bernard Rérat in Forêts de France, n° 528 (novembre 2009)

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2 978 - 16 septembre 2009 - Comment vit-on la crise au sud ? (Bulletin de Problèmes économiques)

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Variability of fire-induced changes in MODIS surface reflectance by land-cover type in Borneo / Jukka Miettinen in International Journal of Remote Sensing IJRS, vol 28 n° 21-22 (November 2007)

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Un système géomatique de préparation aux interventions d'urgence dans le bassin du Mékong : modèle conceptuel de données pour la sécurité et la santé publique lors d'inondations / G. Aube in Revue internationale de géomatique, vol 16 n°3 - 4 (septembre – novembre 2006)

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GPS : de la tectonique à la sismologie / Christophe Vigny (2006) 

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Mapping of the tropical forest cover of insular Southeast Asia from SPOT-4 Vegetation images / Hans-Jürgen Stibig in International Journal of Remote Sensing IJRS, vol 24 n° 18 (September 2003)

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