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A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT / Shengli Tao in Earth System Science Data, vol 15 n° 4 (2023)  

Public [article]  inEarth System Science Data > vol 15 n° 4 (2023) . - pp 1577 - 1596 Titre : A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Zurui Ao, Auteur ; Jean-Pierre Wigneron, Auteur ; Sassan Saatchi, Auteur ; Philippe Ciais, Auteur ; Jérôme Chave, Auteur ; Thuy Le Toan, Auteur ; Pierre-Louis Frison , Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 1577 - 1596 Note générale : bibliographie Data description paper Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] bande Ku [Termes IGN] fusion de données [Termes IGN] image radar moirée [Termes IGN] régression [Termes IGN] série temporelle Résumé : (auteur) Satellite radar backscatter contains unique information on land surface moisture, vegetation features, and surface roughness and has thus been used in a range of Earth science disciplines. However, there is no single global radar data set that has a relatively long wavelength and a decades-long time span. We here provide the first long-term (since 1992), high-resolution (∼8.9 km instead of the commonly used ∼25 km resolution) monthly satellite radar backscatter data set over global land areas, called the long-term, high-resolution scatterometer (LHScat) data set, by fusing signals from the European Remote Sensing satellite (ERS; 1992–2001; C-band; 5.3 GHz), Quick Scatterometer (QSCAT, 1999–2009; Ku-band; 13.4 GHz), and the Advanced SCATterometer (ASCAT; since 2007; C-band; 5.255 GHz). The 6-year data gap between C-band ERS and ASCAT was filled by modelling a substitute C-band signal during 1999–2009 from Ku-band QSCAT signals and climatic information. To this end, we first rescaled the signals from different sensors, pixel by pixel. We then corrected the monthly signal differences between the C-band and the scaled Ku-band signals by modelling the signal differences from climatic variables (i.e. monthly precipitation, skin temperature, and snow depth) using decision tree regression. The quality of the merged radar signal was assessed by computing the Pearson r, root mean square error (RMSE), and relative RMSE (rRMSE) between the C-band and the corrected Ku-band signals in the overlapping years (1999–2001 and 2007–2009). We obtained high Pearson r values and low RMSE values at both the regional (r≥0.92, RMSE ≤ 0.11 dB, and rRMSE ≤ 0.38) and pixel levels (median r across pixels ≥ 0.64, median RMSE ≤ 0.34 dB, and median rRMSE ≤ 0.88), suggesting high accuracy for the data-merging procedure. The merged radar signals were then validated against the European Space Agency (ESA) ERS-2 data, which provide observations for a subset of global pixels until 2011, even after the failure of on-board gyroscopes in 2001. We found highly concordant monthly dynamics between the merged radar signals and the ESA ERS-2 signals, with regional Pearson r values ranging from 0.79 to 0.98. These results showed that our merged radar data have a consistent C-band signal dynamic. The LHScat data set (https://doi.org/10.6084/m9.figshare.20407857; Tao et al., 2023) is expected to advance our understanding of the long-term changes in, e.g., global vegetation and soil moisture with a high spatial resolution. The data set will be updated on a regular basis to include the latest images acquired by ASCAT and to include even higher spatial and temporal resolutions. Numéro de notice : A2023-097 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-15-1577-2023 Date de publication en ligne : 12/04/2023 En ligne : https://doi.org/10.5194/essd-15-1577-2023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103215 [article]

SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery / Marie Ballère in Remote sensing of environment, Vol 252 (January 2021)  

Public [article]  inRemote sensing of environment > Vol 252 (January 2021) . - n° 112159 Titre : SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery Type de document : Article/Communication Auteurs : Marie Ballère , Auteur ; Alexandre Bouvet, Auteur ; Stéphane Mermoz, Auteur ; Thuy Le Toan, Auteur ; Thierry Koleck, Auteur ; Caroline Bedeau, Auteur ; Mathilde André, Auteur ; Elodie Forestier, Auteur ; Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur 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 réel Résumé : (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 [article]

Potential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)  

Public [article]  inRemote sensing > vol 10 n° 12 (December 2018) . - n° 2049 Titre : Potential of Sentinel-1 data for monitoring temperate mixed forest phenology Type de document : Article/Communication Auteurs : Pierre-Louis Frison , Auteur ; Bénédicte Fruneau , Auteur ; Syrine Kmiha, Auteur ; Kamel Soudani, Auteur ; Eric Dufrêne, Auteur ; Thuy Le Toan, Auteur ; Thierry Koleck, Auteur ; Ludovic Villard, Auteur ; Eric Mougin, Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2018 Projets : 3-projet - voir note / Article en page(s) : n° 2049 Note générale : bibliographie This research was funding by the Centre National d’Etudes Spatiales (CNES), grant number DCT/SI/TR/2016-01532 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] arbre caducifolié [Termes IGN] coefficient de rétrodiffusion [Termes IGN] cohérence des données [Termes IGN] données polarimétriques [Termes IGN] Fontainebleau, forêt de (Seine-et-Marne) [Termes IGN] forêt tempérée [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] phénologie [Termes IGN] signature spectrale [Termes IGN] surveillance forestière Résumé : (auteur) In this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France region, France, for the period extending from March 2015 to January 2016. Radar backscattering coefficients, σ0 and the amplitude of temporal interferometric coherence profiles in relation to environmental variables are shown, such as in situ precipitation and air temperature. The high temporal frequency of Sentinel-1 acquisitions (i.e., twelve days, or six, if both Sentinel-1A and B are combined over Europe) and the dual polarization configuration (VV and VH over most land surfaces) made a significant contribution. In particular, the radar backscattering coefficient ratio of VV to VH polarization, σ0VV/σ0VH , showed a well-pronounced seasonality that was correlated with vegetation phenology, as confirmed in comparison to NDVI profiles derived from Landsat-8 (r = 0.77) over stands of deciduous trees. These results illustrate the high potential of Sentinel-1 data for monitoring vegetation, and as these data are not sensitive to the atmosphere, the phenology could be estimated with more accuracy than optical data. These observations will be quantitatively analyzed with the use of electromagnetic models in the near future. Numéro de notice : A2018-669 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs10122049 Date de publication en ligne : 17/12/2018 En ligne : https://doi.org/10.3390/rs10122049 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94271 [article]

Cartographier le relief sous les forêts, et le substrat sous les déserts de sable : les attentes de la mission radar Biomass / Laurent Polidori in XYZ, n° 154 (mars - mai 2018)

Public [article]  inXYZ > n° 154 (mars - mai 2018) . - pp 56 - 61 Titre : Cartographier le relief sous les forêts, et le substrat sous les déserts de sable : les attentes de la mission radar Biomass Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur ; Thierry Koleck, Auteur ; Ludovic Villard, Auteur ; Mhamad El Hage, Auteur ; Philippe Paillou, Auteur ; Thuy Le Toan, Auteur Année de publication : 2018 Article en page(s) : pp 56 - 61 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Missions spatiales [Termes IGN] bande P [Termes IGN] Biomass [Termes IGN] désert [Termes IGN] forêt [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] modèle numérique de terrain [Termes IGN] polarimétrie radar [Termes IGN] radar à antenne synthétique [Termes IGN] tomographie radar Résumé : (Auteur) La mission spatiale Biomass sera lancée par l'Agence spatiale européenne en 2021 avec un radar à synthèse d'ouverture en bande P dans le but de cartographier la biomasse forestière à l'échelle planétaire, ainsi que la hauteur et les dégradations du couvert forestier. Plusieurs produits secondaires sont aussi envisagés, notamment la cartographie 30 du relief sous les forêts et du substrat sous les déserts de sable, qui devraient bénéficier du pouvoir de pénétration des ondes radar en bande P et de l'aptitude de la tomographie à séparer les contributions des différentes couches dans un profil vertical de rétrodiffusion. Ces possibilités ayant été démontrées lors de campagnes aéroportées, la qualité des modèles 3D attendus de la mission Biomass reste à évaluer. Numéro de notice : A2018-090 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89464 [article]

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Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications / Amanda Veloso in Remote sensing of environment, vol 199 (15 September 2017)  

Public [article]  inRemote sensing of environment > vol 199 (15 September 2017) . - pp 415 - 426 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 temporelle Résumé : (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 [article]

Coverage of high biomass forests by the ESA BIOMASS mission under defense restrictions / João M.B. Carreiras in Remote sensing of environment, vol 196 (July 2017)  

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Potential of Sentinel-1 data for vegetation monitoring / Pierre-Louis Frison (2017)

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Radar based classification prior to biomass retrieval from P-Band SAR data / Pierre-Louis Frison (2016)  

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The TropiSAR airborne campaign in French Guiana : objectives, description, and observed temporal behavior of the backscatter signal / P. Dubois-Fernandez in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)  

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Agriculture classification using PolSAR data / H. Skriver (2005)

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Monitoring surface soil moisture in post-harvest rice areas using C-band radar imagery in NorthEast Thailand / S. Kaojarern in Geocarto international, vol 19 n° 3 (September - November 2004)  

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On the retrieving of forest stem volume from VHF SAR data: observation and modeling / P. Melon in IEEE Transactions on geoscience and remote sensing, vol 39 n° 11 (November 2001)  

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Sensitivity of space-borne SAR data to forest parameters over sloping terrain : Theory and experiment / Thierry Castel in International Journal of Remote Sensing IJRS, vol 22 n° 12 (August 2001)  

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Estimation de la hauteur des peuplements forestiers par diffusiomètre radar / J.M. Martinez in Canadian Journal of Forest Research, vol 30 n° 12 (December 2000)  

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Effet de la direction des rangs de semis de maïs sur la réponse radar en bande L / Thuy Le Toan in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 79 - 80 (Octobre 1980)

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