131 results on '"Bouvet, Alexandre"'
Search Results
2. SAR data for tropical forest disturbance alerts in French Guiana: Benefit over optical imagery
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Ballère, Marie, Bouvet, Alexandre, Mermoz, Stéphane, Le Toan, Thuy, Koleck, Thierry, Bedeau, Caroline, André, Mathilde, Forestier, Elodie, Frison, Pierre-Louis, and Lardeux, Cédric
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- 2021
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Catalog
3. Advanced Bayesian Method for Timely Small-Scale Forest Loss Detection in the Brazilian Amazon and Cerrado with Sentinel-1 Time-Series.
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Bottani, Marta, Ferro-Famil, Laurent, Doblas, Juan, Mermoz, Stéphane, Bouvet, Alexandre, and Koleck, Thierry
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The world's forests are undergoing significant changes due to loss and degradation, emphasizing the need for Near Real-Time (NRT) monitoring to prevent further damage. Traditional monitoring methods using optical imagery are hindered by cloud coverage, while newer Synthetic Aperture Radar (SAR) systems, although operational in all weather conditions, face challenges such as sensitivity to soil moisture and the need for spatial filtering to reduce speckle effects. These limitations affect the detection of small-scale forest loss, especially in seasonally variable regions like dry forests and savannas. This paper presents a SAR-based forest disturbance detection method using Bayesian inference. Unlike traditional methods, this approach maintains the native resolution of the data by avoiding spatial filtering. Forest disturbance is modelled as a change-point detection problem within a non-filtered Sentinel-1 time series, where each new observation updates the probability of forest loss by leveraging prior information and a data model. This sequential adaptation ensures robustness against variations and trends, making it effective in monitoring disturbances across diverse forest types, including areas affected by seasonality. The proposed method was tested against other NRT monitoring systems for the year 2020, using small validation polygons (under 1 hectare) in the Brazilian Amazon and Cerrado savanna. Results demonstrate significant improvements in detecting small-scale disturbances and drastically reduced false alarm rates in both biomes. Notably, in the seasonality-sensitive Cerrado, our solution completely outperforms the leading and only existing optical technology. [ABSTRACT FROM AUTHOR] more...
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- 2024
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4. Tackling high biomass in tropical forests through the BIOMASS mission.
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Le Toan, Thuy, Villard, Ludovic, Ho Tong Minh, Dinh, Doblas, Juan, Mermoz, Stephane, Ferro-Famil, Laurent, Koleck, Thierry, Bouvet, Alexandre, Planells, Milena, and Polidori, Laurent
- Abstract
To improve our understanding of the carbon cycle, precise estimates of forest biomass are needed. High values of dense tropical forest biomass are particularly important, as they determine uncertainties in carbon stock assessment and carbon loss due to deforestation and forest degradation. However, estimating Above Ground Biomass (AGB) of tropical forests based on remote sensing systems remains challenging, most existing satellite systems are not sensitive to AGB in the high range. In this paper, we assess the use of P-band SAR tomography technique to provide AGB with reduced uncertainties in the range of 200–400 Mg.ha
−1 . We present the expected contribution of the BIOMASS mission in estimating the carbon loss from deforestation and from forest degradation , and in providing the Digital Elevation Model under dense forests. [ABSTRACT FROM AUTHOR] more...- Published
- 2024
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5. DETER-RT: The new INPE-TropiSCO deforestation monitoring system in the Amazon biome.
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Doblas, Juan, Reis, Mariane Souza, Mermoz, Stéphane, Almeida, Claudio Aparecido, Koleck, Thierry, Messias, Cassiano Gustavo, Soler, Luciana, Bouvet, Alexandre, and Sant'Anna, Sidnei J. S.
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The Amazon biome, undergoing significant deforestation, requires robust monitoring systems for effective management and conservation. This study introduces DETER-RT, a novel deforestation detection system that combines the Synthetic Aperture Radar (SAR)-based DETER-R and the TropiSCO systems to enhance detection capabilities using Sentinel-1 satellite data. DETER-RT utilizes a double-threshold technique to optimize the detection of deforestation by balancing detection accuracy and minimizing false positives across different forest types and conditions in the Amazon. The new system modulates detection thresholds based on the proximity of new disturbances to previously detected deforestation, incorporating a dynamic, regionalized threshold adjustment to cater to the variable characteristics of the Amazon's diverse forest cover. Initial results indicate that DETER-RT provides more timely and accurate warnings compared to existing methods, especially during the fire season, where its performance is less impacted by smoke and haze that typically hinder optical sensors. This approach exemplifies the integration of advanced remote sensing technologies and analytical techniques in environmental monitoring. [ABSTRACT FROM AUTHOR] more...
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- 2024
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6. Forest biomass retrieval approaches from earth observation in different biomes
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Rodríguez-Veiga, Pedro, Quegan, Shaun, Carreiras, Joao, Persson, Henrik J., Fransson, Johan E.S., Hoscilo, Agata, Ziółkowski, Dariusz, Stereńczak, Krzysztof, Lohberger, Sandra, Stängel, Matthias, Berninger, Anna, Siegert, Florian, Avitabile, Valerio, Herold, Martin, Mermoz, Stéphane, Bouvet, Alexandre, Le Toan, Thuy, Carvalhais, Nuno, Santoro, Maurizio, Cartus, Oliver, Rauste, Yrjö, Mathieu, Renaud, Asner, Gregory P., Thiel, Christian, Pathe, Carsten, Schmullius, Chris, Seifert, Frank Martin, Tansey, Kevin, and Balzter, Heiko more...
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- 2019
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7. Remote sensing of β-diversity : Evidence from plant communities in a semi-natural system
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Hoffmann, Samuel, Schmitt, Thomas M., Chiarucci, Alessandro, Irl, Severin D.H., Rocchini, Duccio, Vetaas, Ole R., Tanase, Mihai A., Mermoz, Stéphane, Bouvet, Alexandre, and Beierkuhnlein, Carl
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- 2019
8. Multistability of model and real dryland ecosystems through spatial self-organization
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Bastiaansen, Robbin, Jaïbi, Olfa, Deblauwe, Vincent, Eppinga, Maarten B., Siteur, Koen, Siero, Eric, Mermoz, Stéphane, Bouvet, Alexandre, Doelman, Arjen, and Rietkerk, Max
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- 2018
9. Detection of windthrows and insect outbreaks by L-band SAR: A case study in the Bavarian Forest National Park
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Tanase, Mihai A., Aponte, Cristina, Mermoz, Stéphane, Bouvet, Alexandre, Le Toan, Thuy, and Heurich, Marco
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- 2018
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10. An above-ground biomass map of African savannahs and woodlands at 25 m resolution derived from ALOS PALSAR
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Bouvet, Alexandre, Mermoz, Stéphane, Le Toan, Thuy, Villard, Ludovic, Mathieu, Renaud, Naidoo, Laven, and Asner, Gregory P.
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- 2018
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11. Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications
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Veloso, Amanda, Mermoz, Stéphane, Bouvet, Alexandre, Le Toan, Thuy, Planells, Milena, Dejoux, Jean-François, and Ceschia, Eric
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- 2017
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12. Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring
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Doblas Prieto, Juan, Lima, Lucas, Mermoz, Stephane, Bouvet, Alexandre, Reiche, Johannes, Watanabe, Manabu, Sant Anna, Sidnei, Shimabukuro, Yosio, Doblas Prieto, Juan, Lima, Lucas, Mermoz, Stephane, Bouvet, Alexandre, Reiche, Johannes, Watanabe, Manabu, Sant Anna, Sidnei, and Shimabukuro, Yosio more...
- Abstract
More than half a decade after the launch of the Sentinel-1A C-band SAR satellite, several near real-time forest disturbances detection systems based on backscattering time series analysis have been developed and made operational. Every system has its own particular approach to change detection. Here, we have compared the performance of the main SAR-based near real-time operational forest disturbance detection systems produced by research agencies (INPE, in Brazil, CESBIO, in France, JAXA, in Japan, and Wageningen University, in the Netherlands), and compared them to the state-of-the-art optical algorithm, University of Maryland’s GLAD-S2. We implemented an innovative validation protocol, specially conceived to encompass all the analysed systems, which measured every system’s accuracy and detection speed in four different areas of the Amazon basin. The results indicated that, when parametrized equally, all the Sentinel-1 SAR methods outperformed the reference optical method in terms of sample-count F1-Score, having comparable results among them. The GLAD-S2 optical method showed superior results in terms of user’s accuracy (UA), issuing no false detections, but had a lower producer accuracy (PA, 84.88%) when compared to the Sentinel-1 SAR-based systems (PA∼90%). Wageningen University’s system, RADD, proved to be relatively faster, especially in heavily clouded regions, where RADD warnings were issued 41 days before optical ones, and the one that better performs on small disturbed patches ( more...
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- 2023
13. Above-Ground Biomass estimation: a machine learning approach based on multi-angular L-Band passive microwaves brightness temperatures
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Salazar-Neira, Julio-César, primary, Rodríguez-Fernández, Nemesio, additional, Mialon, Arnaud, additional, Richaume, Phillippe, additional, Mermoz, Stéphane, additional, Kerr, Yann, additional, Bouvet, Alexandre, additional, and Le Thoan, Thuy, additional more...
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- 2023
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14. Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring
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Doblas Prieto, Juan, primary, Lima, Lucas, additional, Mermoz, Stephane, additional, Bouvet, Alexandre, additional, Reiche, Johannes, additional, Watanabe, Manabu, additional, Sant Anna, Sidnei, additional, and Shimabukuro, Yosio, additional more...
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- 2023
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15. Above-Ground Biomass Estimation Based on Multi-Angular L-Band Measurements of Brightness Temperatures
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Salazar-Neira, Julio César, primary, Mialon, Arnaud, additional, Richaume, Philippe, additional, Mermoz, Stéphane, additional, Kerr, Yann H., additional, Bouvet, Alexandre, additional, Le Toan, Thuy, additional, Boitard, Simon, additional, and Rodríguez-Fernández, Nemesio J., additional more...
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- 2023
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16. Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta
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Bouvet, Alexandre and Le Toan, Thuy
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- 2011
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17. Improving Heterogeneous Forest Height Maps by Integrating GEDI-Based Forest Height Information in a Multi-Sensor Mapping Process
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Morin, David, primary, Planells, Milena, additional, Baghdadi, Nicolas, additional, Bouvet, Alexandre, additional, Fayad, Ibrahim, additional, Le Toan, Thuy, additional, Mermoz, Stéphane, additional, and Villard, Ludovic, additional more...
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- 2022
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18. Constraining a land cover map with satellite-based aboveground biomass estimates over Africa
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Marie, Guillaume, primary, Luyssaert, B. Sebastiaan, additional, Dardel, Cecile, additional, Le Toan, Thuy, additional, Bouvet, Alexandre, additional, Mermoz, Stéphane, additional, Villard, Ludovic, additional, Bastrikov, Vladislav, additional, and Peylin, Philippe, additional more...
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- 2022
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19. Forest Biomass From Radar Remote Sensing
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Villard, Ludovic, primary, Le Toan, Thuy, additional, Ho Tong Minh, Dinh, additional, Mermoz, Stéphane, additional, and Bouvet, Alexandre, additional
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- 2016
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20. List of Authors
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Baghdadi, Nicolas, primary, Baret, Frédéric, additional, Bauwens, Sébastien, additional, Betbeder, Julie, additional, Bonnet, Stéphanie, additional, Bouvet, Alexandre, additional, Bréda, Nathalie, additional, Corgne, Samuel, additional, Courault, Dominique, additional, Demarez, Valérie, additional, Ferrant, Sylvain, additional, Gomez, Cécile, additional, Guérif, Martine, additional, Guyon, Dominique, additional, Tang Minh, Dinh Ho, additional, Hubert-Moy, Laurence, additional, Inglada, Jordi, additional, Kemp, Jaco, additional, Lagacherie, Philippe, additional, Lejeune, Philippe, additional, Le Page, Michel, additional, Le Toan, Thuy, additional, Mermoz, Stéphane, additional, Michez, Adrien, additional, Simonneaux, Vincent, additional, Todoroff, Pierre, additional, Veloso, Amanda, additional, Villard, Ludovic, additional, and Zribi, Mehrez, additional more...
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- 2016
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21. Continuous Detection of Forest Loss in Vietnam, Laos, and Cambodia Using Sentinel-1 Data
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Mermoz, Stéphane, primary, Bouvet, Alexandre, additional, Koleck, Thierry, additional, Ballère, Marie, additional, and Le Toan, Thuy, additional
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- 2021
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22. Monitoring of the rice cropping system in the Mekong Delta using ENVISAT/ASAR dual polarization data
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Bouvet, Alexandre, Le Toan, Thuy, and Lam-Dao, Nguyen
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Mekong Delta -- Environmental aspects ,Vegetation mapping -- Technology application ,Synthetic aperture radar -- Usage ,Polarization (Light) -- Evaluation ,Technology application ,Business ,Earth sciences ,Electronics and electrical industries - Abstract
The rice cropping system in Asia is undergoing major changes to cope with increasing demography and changing climate, making rice monitoring a critical issue. Past studies have demonstrated the use of C-band synthetic aperture radar (SAR) data to map rice areas. The methods were based on the temporal change of intensity backscattering coefficient of vertically or horizontally co-polarized data (VV or HH). In this paper, we assess the use of the HH/VV polarization ratio derived from Advanced SAR (ASAR) data from ENVISAT data for the production of rice paddy maps. The approach is based on past knowledge on the polarization behavior of rice canopy, i.e., VV backscattering is much lower than HH during a large part of the rice season, due to the attenuation of the wave by the vertical structure of the plants. The methodology is developed for the Mekong Delta, Vietnam, where a complex cropping pattern is found (one to three crops of rice per year). The approach includes a statistical analysis of the HH/VV distributions of rice and non-rice classes at different dates. The analysis results confirm that HH/VV can be used as classifier and point out the need for relevant speckle filtering prior to classification. A classification method is developed and applied to single-and multidate data sets. The methods are tested at one district of the province of An Giang and extended to the whole province. Comparisons of the mapping results to geographic-information-system land-use data and official agricultural statistics show very good agreement. The method will be further applied to the entire Mekong Delta. Index Terms--(Advanced) Synthetic Aperture Radar (ASAR), Mekong Delta, polarization ratio, rice mapping. more...
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- 2009
23. Supplementary material to "Constraining a land cover map with satellite-based aboveground biomass estimates over Africa"
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Marie, Guillaume, primary, Luyssaert, Sebastiaan, additional, Dardel, Cecile, additional, Le Toan, Thuy, additional, Bouvet, Alexandre, additional, Mermoz, Stéphane, additional, Villard, Ludovic, additional, Bastrikov, Vladislav, additional, and Peylin, Philippe, additional more...
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- 2021
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24. Constraining a land cover map with satellite-based aboveground biomass estimates over Africa
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Marie, Guillaume, primary, Luyssaert, Sebastiaan, additional, Dardel, Cecile, additional, Le Toan, Thuy, additional, Bouvet, Alexandre, additional, Mermoz, Stéphane, additional, Villard, Ludovic, additional, Bastrikov, Vladislav, additional, and Peylin, Philippe, additional more...
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- 2021
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25. Forest disturbances detection in Vietnam, Cambodia and Laos using Sentinel-1 data
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Mermoz, Stéphane, primary, Bouvet, Alexandre, additional, Ballère, Marie, additional, Koleck, Thierry, additional, and Le Toan, Thuy, additional
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- 2021
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26. Near-real-time identification of the drivers of deforestation in French Guiana
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Ballere, Marie, primary, Mermoz, Stephane, additional, Bouvet, Alexandre, additional, Koleck, Thierry, additional, and Le Toan, Thuy, additional
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- 2021
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27. Understanding Dense Time Series of Sentinel-1 Backscatter from Rice Fields: Case Study in a Province of the Mekong Delta, Vietnam
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Phan, Hoa, primary, Le Toan, Thuy, additional, and Bouvet, Alexandre, additional
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- 2021
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28. Use of SAR and Optical Time Series for Tropical Forest Disturbance Mapping
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Hirschmugl, Manuela, primary, Deutscher, Janik, additional, Sobe, Carina, additional, Bouvet, Alexandre, additional, Mermoz, Stéphane, additional, and Schardt, Mathias, additional
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- 2020
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29. Estimation and Mapping of Forest Structure Parameters from Open Access Satellite Images: Development of a Generic Method with a Study Case on Coniferous Plantation
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Morin, David, Planells, Milena, Guyon, Dominique, Villard, Ludovic, Mermoz, Stéphane, Bouvet, Alexandre, Thevenon, Hervé, Dejoux, Jean-François, Le Toan, Thuy, Dedieu, Gérard, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Global Earth Observation, Partenaires INRAE, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) more...
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management tools ,production de bois ,[SDV]Life Sciences [q-bio] ,Science ,forest structure parameters ,forest plantation ,data combinations ,[SDE]Environmental Sciences ,map ,ALOS-PALSAR ,aboveground biomass ,Sentinel ,support vector regression ,carbone ,forêt tempérée - Abstract
International audience; Temperate forests are under climatic and economic pressures. Public bodies, NGOs and the wood industry are looking for accurate, current and affordable data driven solutions to intensify wood production while maintaining or improving long term sustainability of the production, biodiversity, and carbon sequestration. Free tools and open access data have already been exploited to produce accurate quantitative forest parameters maps suitable for policy and operational purposes. These efforts have relied on different data sources, tools, and methods that are tailored for specific forest types and climatic conditions. We hypothesized we could build on these efforts in order to produce a generic method suitable to perform as well or better in a larger range of settings. In this study we focus on building a generic approach to create forest parameters maps and confirm its performance on a test site: a maritime pine (Pinus pinaster) forest located in south west of France. We investigated and assessed options related with the integration of multiple data sources (SAR L- and C-band, optical indexes and spatial texture indexes from Sentinel-1, Sentinel-2 and ALOS-PALSAR-2), feature extraction, feature selection and machine learning techniques. On our test case, we found that the combination of multiple open access data sources has synergistic benefits on the forest parameters estimates. The sensibility analysis shows that all the data participate to the improvements, that reach up to 13.7% when compared to single source estimates. Accuracy of the estimates is as follows: aboveground biomass (AGB) 28% relative RMSE, basal area (BA) 27%, diameter at breast height (DBH) 20%, age 17%, tree density 24%, and height 13%. Forward feature selection and SVR provided the best estimates. Future work will focus on validating this generic approach in different settings. It may prove beneficial to package the method, the tools, and the integration of open access data in order to make spatially accurate and regularly updated forest structure parameters maps effortlessly available to national bodies and forest organizations. more...
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- 2019
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30. An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets:high sensitivity of L-VOD to above-ground biomass in Africa
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Rodríguez-Fernández, Nemesio J., Mialon, Arnaud, Mermoz, Stephane, Bouvet, Alexandre, Richaume, Philippe, Al Bitar, Ahmad, Al-Yaari, Amen, Brandt, Martin Stefan, Kaminski, Thomas, Le Toan, Thuy, Kerr, Yann H., and Wigneron, Jean-Pierre more...
- Abstract
The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (~ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass. more...
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- 2018
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31. Constraining a land cover map with satellite-based aboveground biomass estimates over Africa.
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Marie, Guillaume, Luyssaert, Sebastiaan, Dardel, Cecile, Le Toan, Thuy, Bouvet, Alexandre, Mermoz, Stéphane, Villard, Ludovic, Bastrikov, Vladislav, and Peylin, Philippe
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BIOMASS ,SENSE data ,VEGETATION dynamics ,LAND-atmosphere interactions ,VEGETATION mapping ,LAND cover - Abstract
Most land surface models can either calculate the vegetation distribution and dynamics internally by making use of biogeographical principles or use vegetation maps to prescribe spatial and temporal changes in vegetation distribution. Irrespective of whether vegetation dynamics are simulated or prescribed, it is not practical to represent vegetation across the globe at the species level because of its daunting diversity. This issue can be circumvented by making use of 5 to 20 plant functional types (PFT) by assuming that all species within a single functional type show identical land-atmosphere interactions irrespective of their geographical location. In this study, we hypothesize that remote-sensing based assessments of above-ground biomass can be used to refine discretizing real-world vegetation in PFT maps. Remotely sensed biomass estimates for Africa were used in a Bayesian framework to estimate the probability density distributions of woody, herbaceous, and bare soil fractions for the 15 land cover classes, according to the UN- LCCS typology, present in Africa. Subsequently, the 2.5 and 97.5 percentile of the probability density distributions were used to create 2.5 % and 97.5 % confidence interval PFT maps. Finally the original and refined PFT maps were used to drive biomass and albedo simulations with the ORCHIDEE model. This study demonstrates that remotely sensed biomass data can be used to better constrain PFT maps. Among the advantages of using remotely sensed biomass data were the reduced dependency on expert knowledge and the ability to report the confident interval of the PFT maps. Applying this approach at the global scale, would increase confidence in the PFT maps underlying assessments of present day biomass stocks. [ABSTRACT FROM AUTHOR] more...
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- 2021
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32. Mapping of Rice Varieties and Sowing Date Using X-Band SAR Data
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Phan, Hoa, Le Toan, Thuy, Bouvet, Alexandre, Nguyen, Lam, Pham Duy, Tien, Zribi, Mehrez, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) more...
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Mekong Delta ,rice mapping ,COSMO-SkyMed ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,sowing date ,food and beverages ,lcsh:TP1-1185 ,lcsh:Chemical technology ,Article ,rice variety ,SAR - Abstract
International audience; Rice is a major staple food for nearly half of the world's population and has a considerable contribution to the global agricultural economy. While spaceborne Synthetic Aperture Radar (SAR) data have proved to have great potential to provide rice cultivation area, few studies have been performed to provide practical information that meets the user requirements. In rice growing regions where the inter-field crop calendar is not uniform such as in the Mekong Delta in Vietnam, knowledge of the start of season on a field basis, along with the planted rice varieties, is very important for correct field management (timing of irrigation, fertilization, chemical treatment, harvest), and for market assessment of the rice production. The objective of this study is to develop methods using SAR data to retrieve in addition to the rice grown area, the sowing date, and the distinction between long and short cycle varieties. This study makes use of X-band SAR data from COSMO-SkyMed acquired from 19 August to 23 November 2013 covering the Chau Thanh and Thoai Son districts in An Giang province, Viet Nam, characterized by a complex cropping pattern. The SAR data have been analyzed as a function of rice parameters, and the temporal and polarization behaviors of the radar backscatter of different rice varieties have been interpreted physically. New backscatter indicators for the detection of rice paddy area, the estimation of the sowing date, and the mapping of the short cycle and long cycle rice varieties have been developed and assessed. Good accuracy has been found with 92% in rice grown area, 96% on rice long or short cycle, and a root mean square error of 4.3 days in sowing date. The results have been discussed regarding the generality of the methods with respect to the rice cultural practices and the SAR data characteristics. more...
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- 2018
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33. Impacts of the forest definitions adopted by African countries on carbon conservation
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Mermoz, Stéphane, Bouvet, Alexandre, Le Toan, Thuy, Herold, Martin, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Wageningen University and Research [Wageningen] (WUR), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) more...
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carbon stocks ,savannahs ,Laboratory of Geo-information Science and Remote Sensing ,[SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry ,tropical forestry ,[SDE]Environmental Sciences ,Laboratorium voor Geo-informatiekunde en Remote Sensing ,PE&RC ,REDD+ - Abstract
International audience; In this paper, we aim to assess the impacts of the forest definitions adopted by each African country involved in the global climate change programmes of the United Nations on national carbon emission estimations. To do so, we estimate the proportion of national carbon stocks and tree cover loss that are found in areas considered to be non-forest areas. These non-forest areas are defined with respect to a threshold on the percentage of tree cover adopted by each country. Using percent tree cover and aboveground biomass maps derived from remote sensing data, we quantitatively show that in many countries, a large proportion of carbon stocks are found in non-forest areas, where a large amount of tree cover loss can also occur. We further found that under the REDD+ framework (reduced deforestation, reduced degradation, enhancement and conservation of forest carbon stocks, sustainable management of forests), some partner countries have proposed activities related to only reducing deforestation, even when a large proportion of their carbon stocks are stored outside forests. This situation may represent a limitation of the efficiency of the REDD+ mechanism, and could be avoided if these countries choose a lower tree cover threshold for their definition of forests and/or if they were are engaged in other activities. more...
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- 2018
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34. Detection of Irrigated Crops from Sentinel-1 and Sentinel-2 Data to Estimate Seasonal Groundwater Use in South India
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Ferrant, Sylvain, Selles, Adrien, Le Page, Michel, Herrault, Pierre-Alexis, Pelletier, Charlotte, Al-Bitar, Ahmad, Mermoz, Stéphane, Gascoin, Simon, Bouvet, Alexandre, Saqalli, Mehdi, Dewandel, Benoît, Caballero, Yvan, Ahmed, Shakeel, Maréchal, Jean-Christophe, Kerr, Yann, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC), Géographie de l'environnement (GEODE), Université Toulouse - Jean Jaurès (UT2J)-Centre National de la Recherche Scientifique (CNRS), Structure et fonctionnement des systèmes hydriques continentaux (SISYPHE), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Indo-French Centre for Groundwater Research (IFCGR), Bureau de Recherches Géologiques et Minières (BRGM) (BRGM)-National Geophysical Research Institute [Hyderabad] (NGRI), Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie]), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE)-MINES ParisTech - École nationale supérieure des mines de Paris-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Indo-French Center for Groundwater Research (IFCGR), Institut de Recherche pour le Développement ( IRD [Nouvelle-Calédonie] ), Université Pierre et Marie Curie - Paris 6 ( UPMC ), Centre d'études spatiales de la biosphère ( CESBIO ), Université Paul Sabatier - Toulouse 3 ( UPS ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Observatoire Midi-Pyrénées ( OMP ) -Centre National d'Etudes Spatiales ( CNES ) -Centre National de la Recherche Scientifique ( CNRS ), Géographie de l'environnement ( GEODE ), Centre National de la Recherche Scientifique ( CNRS ) -Université Toulouse - Jean Jaurès ( UT2J ), Institut d'Electronique et de Télécommunications de Rennes ( IETR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ) -SUPELEC-Centre National de la Recherche Scientifique ( CNRS ), Structure et fonctionnement des systèmes hydriques continentaux ( SISYPHE ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -École pratique des hautes études ( EPHE ) -MINES ParisTech - École nationale supérieure des mines de Paris-Centre National de la Recherche Scientifique ( CNRS ), JRC Institute for Environment and Sustainability ( IES ), European Commission - Joint Research Centre [Ispra] ( JRC ), Bureau de Recherches Géologiques et Minières (BRGM) ( BRGM ), and Indo-French Centre for Groundwater Research ( IFCGR ) more...
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Science ,agro-hydrology ,groundwater shortage monitoring ,[SDE.ES]Environmental Sciences/Environmental and Society ,[ SDE ] Environmental Sciences ,[SDE]Environmental Sciences ,Sentinel-1 ,radar and optical synergy ,Sentinel-2 ,crop cover mapping ,[ SDE.ES ] Environmental Sciences/Environmental and Society ,ComputingMilieux_MISCELLANEOUS ,random forest ,rice irrigation - Abstract
Indian agriculture relies on monsoon rainfall and irrigation from surface and groundwater. The interannual variability of monsoon rainfalls is high, which forces South Indian farmers to adapt their irrigated areas to local water availability. In this study, we have developed and tested a methodology for monitoring these spatiotemporal variations using Sentinel-1 and -2 observations over the Kudaliar catchment, Telangana State (~1000 km2). These free radar and optical data have been acquired since 2015 on a weekly basis over continental areas, at a high spatial resolution (10–20 m) that is well adapted to the small areas of South Indian field crops. A machine learning algorithm, the Random Forest method, was used over three growing seasons (January to March and July to November 2016 and January to March 2017) to classify small patches of inundated rice paddy, maize, and other irrigated crops, as well as surface water stored in the small reservoirs scattered across the landscape. The crop production comprises only irrigated crops (less than 20% of the areas) during the dry season (Rabi, December to March), to which rain-fed cotton is added to reach 60% of the areas during the monsoon season (Kharif, June to November). Sentinel-1 radar backscatter provides useful observations during the cloudy monsoon season. The lowest irrigated area totals were found during Rabi 2016 and Kharif 2016, accounting for 3.5 and 5% with moderate classification confusion. This confusion decreases with increasing areas of irrigated crops during Rabi 2017. During this season, 16% of rice and 6% of irrigated crops were detected after the exceptional rainfalls observed in September. Surface water in small surface reservoirs reached 3% of the total area, which corresponds to a high value. The use of both Sentinel datasets improves the method accuracy and strengthens our confidence in the resulting maps. This methodology shows the potential of automatically monitoring, in near real time, the high short term variability of irrigated area totals in South India, as a proxy for estimating irrigated water and groundwater needs. These are estimated over the study period to range from 49.5 ± 0.78 mm (1.5% uncertainty) in Rabi 2016, and 44.9 ± 2.9 mm (6.5% uncertainty) in the Kharif season, to 226.2 ± 5.8 mm (2.5% uncertainty) in Rabi 2017. This variation must be related to groundwater recharge estimates that range from 10 mm to 160 mm·yr−1 in the Hyderabad region. These dynamic agro-hydrological variables estimated from Sentinel remote sensing data are crucial in calibrating runoff, aquifer recharge, water use and evapotranspiration for the spatially distributed agro-hydrological models employed to quantify the impacts of agriculture on water resources. more...
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- 2017
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35. Remote sensing of β‐diversity: Evidence from plant communities in a semi‐natural system
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Hoffmann, Samuel, primary, Schmitt, Thomas M., additional, Chiarucci, Alessandro, additional, Irl, Severin D. H., additional, Rocchini, Duccio, additional, Vetaas, Ole R., additional, Tanase, Mihai A., additional, Mermoz, Stéphane, additional, Bouvet, Alexandre, additional, and Beierkuhnlein, Carl, additional more...
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- 2018
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36. Use of the SAR Shadowing Effect for Deforestation Detection with Sentinel-1 Time Series
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Bouvet, Alexandre, primary, Mermoz, Stéphane, additional, Ballère, Marie, additional, Koleck, Thierry, additional, and Le Toan, Thuy, additional
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- 2018
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37. An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: high sensitivity of L-VOD to above-ground biomass in Africa
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Rodríguez-Fernández, Nemesio J., primary, Mialon, Arnaud, additional, Mermoz, Stephane, additional, Bouvet, Alexandre, additional, Richaume, Philippe, additional, Al Bitar, Ahmad, additional, Al-Yaari, Amen, additional, Brandt, Martin, additional, Kaminski, Thomas, additional, Le Toan, Thuy, additional, Kerr, Yann H., additional, and Wigneron, Jean-Pierre, additional more...
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- 2018
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38. The high sensitivity of SMOS L-Band vegetation optical depth to biomass
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Rodríguez-Fernández, Nemesio J., primary, Mialon, Arnaud, additional, Mermoz, Stephane, additional, Bouvet, Alexandre, additional, Richaume, Philippe, additional, Al Bitar, Ahmad, additional, Al-Yaari, Amen, additional, Brandt, Martin, additional, Kaminski, Thomas, additional, Le Toan, Thuy, additional, Kerr, Yann H., additional, and Wigneron, Jean-Pierre, additional more...
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- 2018
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39. Supplementary material to "The high sensitivity of SMOS L-Band vegetation optical depth to biomass"
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Rodríguez-Fernández, Nemesio J., primary, Mialon, Arnaud, additional, Mermoz, Stephane, additional, Bouvet, Alexandre, additional, Richaume, Philippe, additional, Al Bitar, Ahmad, additional, Al-Yaari, Amen, additional, Brandt, Martin, additional, Kaminski, Thomas, additional, Le Toan, Thuy, additional, Kerr, Yann H., additional, and Wigneron, Jean-Pierre, additional more...
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- 2018
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40. 9 - Forest Biomass From Radar Remote Sensing
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Villard, Ludovic, Le Toan, Thuy, Ho Tong Minh, Dinh, Mermoz, Stéphane, and Bouvet, Alexandre
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- 2016
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41. Multistability of model and real dryland ecosystems through spatial self-organization
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Environmental Sciences, Sub Physical Oceanography, Spatial Ecology and Global Change, Afd Marine and Atmospheric Research, Bastiaansen, Robbin, Jaïbi, Olfa, Deblauwe, Vincent, Eppinga, Maarten B, Siteur, Koen, Siero, Eric, Mermoz, Stéphane, Bouvet, Alexandre, Doelman, Arjen, Rietkerk, Max, Environmental Sciences, Sub Physical Oceanography, Spatial Ecology and Global Change, Afd Marine and Atmospheric Research, Bastiaansen, Robbin, Jaïbi, Olfa, Deblauwe, Vincent, Eppinga, Maarten B, Siteur, Koen, Siero, Eric, Mermoz, Stéphane, Bouvet, Alexandre, Doelman, Arjen, and Rietkerk, Max more...
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- 2018
42. Agro-hydrology from Space
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Ferrant, Sylvain, Kerr, Yann, Selles, Adrien, Stephane Mermoz, Bouvet, Alexandre, Page, Michel Le, Al-Bitar, Ahmad, Mehrez Zribi, Gascoin, Simon, Jean-Christophe Maréchal, and Durand, Patrick
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- 2017
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43. The K&C PALSAR Mosaic of the African Continent: Processing Issues and First Thematic Results
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De, Grandi Gianfranco D., Bouvet, Alexandre, Lucas, Richard M., Monaco, Stefano, Rosenqvist, Ake, Shimada, Masanobu, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Department of Geography and Earth Sciences (DGES), Aberystwyth University, Earth Observation Research Center [Saitama] (EORC), Japan Aerospace Exploration Agency [Tokyo] (JAXA), sarmap, solo Earth Observation (soloEO), and soloEO more...
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Synthetic aperture radar ,010504 meteorology & atmospheric sciences ,0211 other engineering and technologies ,Climate change ,Mosaic (geodemography) ,02 engineering and technology ,01 natural sciences ,Space exploration ,law.invention ,law ,Electrical and Electronic Engineering ,Radar ,021101 geological & geomatics engineering ,0105 earth and related environmental sciences ,Remote sensing ,Continental-scale radar mapping ,15. Life on land ,synthetic aperture radar (SAR) mosaic processing ,vegetation monitoring ,Geography ,Thematic map ,13. Climate action ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,General Earth and Planetary Sciences ,Radiometry ,Phased-Array L-Band Synthetic Aperture Radar (PALSAR) ,Satellite - Abstract
International audience; The Japan Space Exploration Agency Kyoto and Carbon (K&C) Initiative seeks to demonstrate the potential of the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data for addressing regional applications relating to climate change, carbon cycle science, and environmental conservation. This paper outlines the generation of a regional dual-polarization (HH and HV) mosaic for the entire African continent at spatial resolution on the order of 100 m. The main computational and radar science issues undertaken to generate a seamless mosaic with good radiometric and geometric accuracy are summarized. Preliminary investigations into the thematic information provided by the K&C Africa mosaic and comparisons with the JERS-1 SAR mosaic generated as part of the Global Rain Forest Mapping Project are reported, with emphasis placed on characterizing and detecting change in forests and savannas. more...
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- 2011
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44. Permeability Study of API Class G and B Cements Considering Seawater and WBM Contamination
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Le-Minous, Jean Christophe, additional, Mutti, Didier, additional, Bouvet, Alexandre, additional, Unanue-Rodriguez, Iker, additional, Chang, Andy, additional, Massie, Iain, additional, Xiao, Erin, additional, and Schnell, Ernst, additional more...
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- 2017
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45. Remote sensing of β‐diversity: Evidence from plant communities in a semi‐natural system.
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Feilhauer, Hannes, Hoffmann, Samuel, Schmitt, Thomas M., Irl, Severin D. H., Beierkuhnlein, Carl, Chiarucci, Alessandro, Rocchini, Duccio, Vetaas, Ole R., Mermoz, Stéphane, Bouvet, Alexandre, and Tanase, Mihai A. more...
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BIOGEOGRAPHY ,LIDAR ,PLANT communities ,REMOTE sensing ,PLANTS - Abstract
Question: Do remote sensing signals represent β‐diversity? Does β‐diversity agree with community types? Location: UNESCO Man and the Biosphere Reserve, La Palma, Canary Islands. Methods: We recorded perennial, vascular plant species abundances in 69 plots (10 m × 10 m) in three pre‐defined community types along an elevational gradient of 2,400 m: succulent scrubland, Pinus canariensis forest and subalpine scrubland. The remote sensing data consists of structural variables from airborne Light Detection and Ranging (LiDAR) and multispectral variables from a time series of Sentinel‐2 (S2) images. Non‐metric Multidimensional Scaling was used to assess β‐diversity between plots. K‐means unsupervised clustering was applied to remote sensing variables to distinguish three community types. We subsequently quantified the explanatory power of S2 and LiDAR variables representing β‐diversity via the Mantel test, variation partitioning and multivariate analysis of variance. We also investigated the sensitivity of results to grain size of remote sensing data (20, 40, 60 m). Results: The β‐diversity between the succulent and pine community is high, whereas the β‐diversity between the pine and subalpine community is low. In the wet season, up to 85% of β‐diversity is reflected by remote sensing variables. The S2 variables account for more explanatory power than the LiDAR variables. The explanatory power of LiDAR variables increases with grain size, whereas the explanatory power of S2 variables decreases. Conclusion: At the lower ecotone, β‐diversity agrees with the pre‐defined community distinction, while at the upper ecotone the community types cannot be clearly separated by compositional dissimilarity alone. The high β‐diversity between the succulent scrub and pine forest results from positive feedback switches of P. canariensis, being a fire‐adapted, key tree species. In accordance with the spectral variation hypothesis, remote sensing signals can adequately represent β‐diversity for a large extent, in a short time and at low cost. However, in‐situ sampling is necessary to fully understand community composition. Nature conservation requires such interdisciplinary approaches. We assessed beta diversity between assemblages of perennial and vascular plant species along an elevational gradient of 2,400 m, crossing three community types on La Palma, Canary Islands. Remote sensing variables were derived from LiDAR and a time series of Sentinel‐2 imagery. In the wet season, up to 85% of beta diversity is represented by RS signals. [ABSTRACT FROM AUTHOR] more...
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- 2019
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46. The high sensitivity of SMOS L-Band vegetation optical depth to biomass.
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Rodríguez-Fernández, Nemesio J., Mialon, Arnaud, Mermoz, Stephane, Bouvet, Alexandre, Richaume, Philippe, Al Bitar, Ahmad, Thuy Le Toan, Kerr, Yann H., Al-Yaari, Amen, Wigneron, Jean-Pierre, Brandt, Martin, and Kaminski, Thomas more...
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VEGETATION dynamics ,SENSITIVITY analysis ,BIOMASS ,OPTICAL depth (Astrophysics) ,SOIL moisture ,SEAWATER salinity - Abstract
The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (~ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass. [ABSTRACT FROM AUTHOR] more...
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- 2018
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47. K&C Science Report-Phase II Forest biomass assessment in Vietnam using ALOS/PALSAR
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Toan, Thuy Le, Ngoc, Tran Tuan, Nguyen, Lam Dao, Villard, Ludovic, Bouvet, Alexandre, Rosenqvist, Ake, and Nguyen, Nga
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- 2011
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48. Effects of changing cultural practices on C-band SAR backscatter using Envisat ASAR data in the Mekong River Delta
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Lam-Dao, Nguyen, Le Toan, Thuy, Apan, Armando, Bouvet, Alexandre, Young, Frank, Le-Van, Trung, GIS and Remote Sensing Research Center, Ho Chi Minh City Institute of Resources Geography, University of Southern Queensland (USQ), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Faculty of Engineering and Surveying, GIS and Remote Sensing Center, HoChiMinh City Institute of Resources Geography, Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) more...
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cultural practices ,rice ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,Mekong River Delta ,mapping ,SAR - Abstract
International audience; Changes in rice cultivation systems have been observed in the Mekong River Delta, Vietnam. Among the changes in cultural practices, the change from transplanting to direct sowing, the use of water-saving technology, and the use of high production method could have impacts on radar remote sensing methods previously developed for rice monitoring. Using Envisat (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) data over the province of An Giang, this study showed that the radar backscattering behaviour is much different from that of the reported traditional rice. At the early stage of the season, direct sowing on fields with rough and wet soil surface provides very high backscatter values for HH (Horizontal transmit - Horizontal receive polarisation) and VV (Vertical transmit - Vertical receive polarisation) data, as a contrast compared to the very low backscatter of fields covered with water before emergence. The temporal increase of the backscatter is therefore not observed clearly over direct sowing fields. Hence, the use of the intensity temporal change as a rice classifier proposed previously may not apply. Due to the drainage that occurs during the season, HH, VV and HH/VV are not strongly related to biomass, in contrast with past results. However, HH/VV ratio could be used to derive the rice/non-rice classification algorithm for all conditions of rice fields in the test province. The mapping results using the HH/VV polarization ratio at a single date in the middle period of the rice season were assessed using statistical data at different districts in the province, where very high accuracy was found. The method can be applied to other regions, provided that the synthetic aperture radar data are acquired during the peak period of the rice season, and that few training fields provide adjusted threshold values used in the method. more...
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- 2009
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49. Télédétection radar appliquée au suivi des rizières. Méthodes utilisant le rapport des intensités de rétrodiffusion
- Author
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Bouvet, Alexandre, Centre d'études spatiales de la biosphère (CESBIO), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Paul Sabatier - Toulouse III, Thuy Le Toan(thuy.letoan@cesbio.cnes.fr), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS) more...
- Subjects
rizières ,télédétection ,rapport de polarisation ,SAR (Synthetic Aperture Radar) ,temporal change ,rice fields ,remote sensing ,polarisation ratio ,rapport d'intensité ,classification ,changement temporel ,intensity ratio ,[SDU.OTHER]Sciences of the Universe [physics]/Other ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
Because of the importance of rice in global food security and of the role of rice paddies in methane emissions, a large-scale near-real-time monitoring system of rice fields appears to be particularly useful. The objective of this work is to develop methods aiming at an effective use of remote sensing data from past and future satellites for rice fields monitoring. Radar imagery is preferred to optical imagery, due to its all-weather ability. Two methods are considered, both involving a C-band SAR intensity ratio as a classification feature: the HH/VV polarization ratio and the co-polarized temporal change HHdate2/HHdate1. First, a statistical study of intensity ratios is done, leading to the development of an error model that estimates the performance of the classification methods. The error model is also used to assess the impact of SAR system parameters (calibration, ambiguity ratio, revisit frequency) on the classification accuracy. Then, these classification methods are applied to two datasets acquired by the ASAR instrument onboard ENVISAT over the Mekong Delta, Vietnam, in order to map rice fields at two scales. The first approach relies on the use of the HH/VV polarization ratio calculated from the Alternating Polarization mode of ASAR, and is applied to produce a rice map covering one province in the delta. The second approach uses the HH temporal change of Wide-Swath mode images from ASAR, and allows mapping rice fields over the whole delta. Both methods are validated with success through the use of the cultivated areas reported in national statistics.; En raison de l'importance du riz dans l'alimentation mondiale et du rôle des rizières dans les émissions de méthane, un suivi à grande échelle et en temps quasi-réel des surfaces cultivées en riz semble particulièrement utile. L'objectif de cette thèse est de développer des méthodes permettant une utilisation effective des données de télédétection des satellites présents et futurs pour le suivi des rizières. L'imagerie radar est privilégiée car elle permet des acquisitions sous toutes les conditions météorologiques, contrairement à l'imagerie optique. Deux méthodes sont retenues qui font intervenir un rapport d'intensité de deux images SAR en bande C : le rapport de polarisation HH/VV ou le changement temporel en co-polarisation HHdate2/HHdate1. Dans un premier temps, une étude statistique des rapports d'intensité de rétrodiffusion est effectuée, qui conduit au développement d'un modèle d'erreur permettant d'estimer la performance des méthodes de classification. Ce modèle d'erreur est également utilisé pour évaluer l'impact des paramètres des systèmes SAR (Synthetic Aperture Radar) sur la performance de la classification. Il s'agit des paramètres concernant l'étalonnage, l'ambiguïté, la fréquence de revisite. Dans un second temps, les méthodes de classification ainsi développées sont appliquées à deux jeux de données de l'instrument ASAR du satellite ENVISAT sur le delta du Mékong au Vietnam, pour faire la cartographie des rizières à deux échelles différentes. La première méthode repose sur l'utilisation du rapport HH/VV à partir de données du mode Alternating Polarization d'ASAR, qui permet de produire une carte de rizières couvrant une province du delta. La seconde méthode tire parti du changement temporel de HH sur des images du mode Wide-Swath d'ASAR, et est utilisée pour cartographier les rizières de l'ensemble du delta. Les deux méthodes sont validées avec succès en utilisant les surfaces cultivées données par les statistiques nationales. more...
- Published
- 2009
50. Radar remote sensing applied to rice fields monitoring. Methods using a backscatter intensity ratio
- Author
-
Bouvet, Alexandre, Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier - Toulouse III, and Thuy Le Toan(thuy.letoan@cesbio.cnes.fr) more...
- Subjects
rizières ,télédétection ,rapport de polarisation ,SAR (Synthetic Aperture Radar) ,temporal change ,rice fields ,remote sensing ,polarisation ratio ,rapport d'intensité ,classification ,changement temporel ,intensity ratio ,[SDU.OTHER]Sciences of the Universe [physics]/Other ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing - Abstract
Because of the importance of rice in global food security and of the role of rice paddies in methane emissions, a large-scale near-real-time monitoring system of rice fields appears to be particularly useful. The objective of this work is to develop methods aiming at an effective use of remote sensing data from past and future satellites for rice fields monitoring. Radar imagery is preferred to optical imagery, due to its all-weather ability. Two methods are considered, both involving a C-band SAR intensity ratio as a classification feature: the HH/VV polarization ratio and the co-polarized temporal change HHdate2/HHdate1. First, a statistical study of intensity ratios is done, leading to the development of an error model that estimates the performance of the classification methods. The error model is also used to assess the impact of SAR system parameters (calibration, ambiguity ratio, revisit frequency) on the classification accuracy. Then, these classification methods are applied to two datasets acquired by the ASAR instrument onboard ENVISAT over the Mekong Delta, Vietnam, in order to map rice fields at two scales. The first approach relies on the use of the HH/VV polarization ratio calculated from the Alternating Polarization mode of ASAR, and is applied to produce a rice map covering one province in the delta. The second approach uses the HH temporal change of Wide-Swath mode images from ASAR, and allows mapping rice fields over the whole delta. Both methods are validated with success through the use of the cultivated areas reported in national statistics.; En raison de l'importance du riz dans l'alimentation mondiale et du rôle des rizières dans les émissions de méthane, un suivi à grande échelle et en temps quasi-réel des surfaces cultivées en riz semble particulièrement utile. L'objectif de cette thèse est de développer des méthodes permettant une utilisation effective des données de télédétection des satellites présents et futurs pour le suivi des rizières. L'imagerie radar est privilégiée car elle permet des acquisitions sous toutes les conditions météorologiques, contrairement à l'imagerie optique. Deux méthodes sont retenues qui font intervenir un rapport d'intensité de deux images SAR en bande C : le rapport de polarisation HH/VV ou le changement temporel en co-polarisation HHdate2/HHdate1. Dans un premier temps, une étude statistique des rapports d'intensité de rétrodiffusion est effectuée, qui conduit au développement d'un modèle d'erreur permettant d'estimer la performance des méthodes de classification. Ce modèle d'erreur est également utilisé pour évaluer l'impact des paramètres des systèmes SAR (Synthetic Aperture Radar) sur la performance de la classification. Il s'agit des paramètres concernant l'étalonnage, l'ambiguïté, la fréquence de revisite. Dans un second temps, les méthodes de classification ainsi développées sont appliquées à deux jeux de données de l'instrument ASAR du satellite ENVISAT sur le delta du Mékong au Vietnam, pour faire la cartographie des rizières à deux échelles différentes. La première méthode repose sur l'utilisation du rapport HH/VV à partir de données du mode Alternating Polarization d'ASAR, qui permet de produire une carte de rizières couvrant une province du delta. La seconde méthode tire parti du changement temporel de HH sur des images du mode Wide-Swath d'ASAR, et est utilisée pour cartographier les rizières de l'ensemble du delta. Les deux méthodes sont validées avec succès en utilisant les surfaces cultivées données par les statistiques nationales. more...
- Published
- 2009
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