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23 results on '"Binh Pham-Duc"'

1. Remote sensing assessment of wildfire using high-resolution PlanetScope satellite observations: A case study on Co Tien Mountain, Nha Trang City, Vietnam

Author

Binh Pham-Duc and Ho Nguyen

Subjects
dndvi, ndvi, planetscope satellite, vietnam mountains, wildfire mapping, Environmental effects of industries and plants, TD194-195
Abstract

In this study, high spatial resolution (3 m) PlanetScope (PS) imagery was utilized to map burned areas caused by a wildfire occurring on January 10, 2024, on Co Tien Mountain in Nha Trang city, Khanh Hoa province, South Central Coast of Vietnam. A pre-fire image, acquired ten days earlier, on December 31, 2023, and a post-fire one, acquired nearly one month after, on February 04, 2024, were used to create pre- and post-fire Normalized Difference Vegetation Index (NDVI) maps of the study area, then the difference of NDVI (dNDVI). A threshold (T = 0.20), proposed by the author, was applied to the histogram of the dNDVI product to classify the study area into two clusters: burned pixels (dNDVI > T) and unburned pixels (dNDVI

Published
2024
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2. Strengthening of the hydrological cycle in the Lake Chad Basin under current climate change

Author

Florence Sylvestre, Abdallah Mahamat-Nour, Toussaint Naradoum, Matias Alcoba, Laetitia Gal, Adrien Paris, Jean-François Cretaux, Binh Pham-Duc, Christophe Lescoulier, Romain Recouvreur, Mahmoud Mahamat Ahmat, and Djergo Gaya

Subjects
Medicine, Science
Abstract

Abstract Central Sahel is affected by a reinforcement of rainfall since the beginning of 1990s. This increase in rainfall is affected by high inter-annual variability and is characterized by extreme rain events causing floods of unprecedented magnitude. However, few studies have been carried out on these extreme events. Moreover, with current climate change expected to strengthen the hydrological cycle, we don’t know if these events could become more frequent. Here, we report the hydrological changes that currently occur in the Lake Chad basin. Based on ground observations and satellite data, we focused on the 2022 flood event, demonstrating that it was the most important event from the last 60 years, comparable to what occurred during the last wet period between the 1950s and the 1960s. We showed that under this precipitation regime and if warming is not regulated at a global scale, the return period of the 2022 major riverine flood is expected to be between 2 and 5 years. By using modelling experiments, our study also suggested that in the next decade, future flow rates of the main rivers draining the Lake Chad basin could reach the values observed in the 1950s. These results strongly suggest anticipating water management in a context of poor infrastructural development.

Published
2024
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3. Comparison of multi-source satellite remote sensing observations for monitoring the variations of small lakes: a case study of Dai Lai Lake (Vietnam)

Author

Binh Pham-Duc

Subjects
dai lai lake, lake mapping, lake monitoring, planetscope, sentinel-1, sentinel-2, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350
Abstract

This study compares the capability of Sentinel-1, Sentinel-2, and PlanetScope (PS) satellites in monitoring the variations of surface water of Dai Lai Lake, located in North Vietnam, for the 2018–2023 period. The analysis involves the utilization of Google Earth Engine to partially process Sentinel-1 and Sentinel-2 observations, while PS observations are processed using local computers, to generate VH-polarized backscatter coefficient, Normalized Difference Water Index (NDWI), and Modified of Normalized Difference Water Index (MNDWI) maps. The method for making binary water/non-water maps primarily employs the Otsu algorithm on each single map derived from the previous step. Findings reveal that the lake's water extent remains relatively stable over the 6-year period, and is not strongly affected by the seasonal cycle. Although the spatial distribution patterns of the lake exhibit significant similarity, average water extent of the lake derived from 3-m resolution PS imagery is about 2.17 and 5.60% more than that obtained from 10-m resolution Sentinel-2 and Sentinel-1 imagery, respectively. PS observations are effective for monitoring small lakes, but it is advised to check the quality of its NIR band. Sentinel-2 observations prove great effectiveness for lake monitoring, using both NDWI and MNDWI. For Sentinel-1 observations, potential misclassifications could arise due to similarities in VH-polarized backscatter coefficients between water surfaces and other flat surfaces. HIGHLIGHTS The lake's surface water extent maps derived from PlanetScope is about 5.60 and 2.17% more than that derived from Sentinel-1 and Sentinel-2.; NDWI and MNDWI provide similar results in small lake mapping and monitoring.; Quality of the PlanetScope NIR wavelength is not always as good as that from Sentinel-2 satellite.; Many similarities in Sentinel-1 backscatter coefficients between water surfaces and other flat surfaces.;

Published
2024
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4. Monitoring Lake Volume Variation from Space Using Satellite Observations—A Case Study in Thac Mo Reservoir (Vietnam)

Author

Binh Pham-Duc, Frederic Frappart, Quan Tran-Anh, Son Tong Si, Hien Phan, Son Nguyen Quoc, Anh Pham Le, and Bach Do Viet

Subjects
lake volume monitoring, satellite data, Sentinel-1, Sentinel-2, Jason-3, altimetry data, Science
Abstract

This study estimates monthly variation of surface water volume of Thac Mo hydroelectric reservoir (located in South Vietnam), during the 2016–2021 period. Variation of surface water volume is estimated based on variation of surface water extent, derived from Sentinel-1 observations, and variation of surface water level, derived from Jason-3 altimetry data. Except for drought years in 2019 and 2020, surface water extent of Thac Mo reservoir varies in the range 50–100 km2, while its water level varies in the range 202–217 m. Correlation between these two components is high (R = 0.948), as well as correlation between surface water maps derived from Sentinel-1 and free-cloud Sentinel-2 observations (R = 0.98), and correlation between surface water level derived from Jason-3 altimetry data and from in situ measurement (R = 0.99; RMSE = 0.86 m). We showed that water volume of Thac Mo reservoir varies between −0.3 and 0.4 km3 month−1, and it is in a very good agreement with in situ measurement (R = 0.95; RMSE = 0.0682 km3 month−1). This study highlights the advantages in using different types of satellite observations and data for monitoring variation of lakes’ water storage, which is very important for regional hydrological models. Similar research can be applied to monitor lakes in remote areas where in situ measurements are not available, or cannot be accessed freely.

Published
2022
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5. Surface Water Evolution (2001–2017) at the Cambodia/Vietnam Border in the Upper Mekong Delta Using Satellite MODIS Observations

Author

Filipe Aires, Jean-Philippe Venot, Sylvain Massuel, Nicolas Gratiot, Binh Pham-Duc, and Catherine Prigent

Subjects
wetlands/inundation, satellite remote sensing, trend analysis, hydrology, vietnam, cambodia, water control, Science
Abstract

Studying the spatial and temporal distribution of surface water resources is critical, especially in highly populated areas and in regions under climate change pressure. There is an increasing number of satellite Earth observations that can provide information to monitor surface water at global scale. However, mapping surface waters at local and regional scales is still a challenge for numerous reasons (insufficient spatial resolution, vegetation or cloud opacity, limited time-frequency or time-record, information content of the instrument, lack in global retrieval method, interpretability of results, etc.). In this paper, we use 17 years of the MODIS (MODerate-resolution Imaging Spectro-radiometer) observations at a 8-day resolution. This satellite dataset is combined with ground expertise to analyse the evolution of surface waters at the Cambodia/Vietnam border in the Upper Mekong Delta. The trends and evolution of surface waters are very significant and contrasted, illustrating the impact of agriculture practices and dykes construction. In most of the study area in Cambodia. surface water areas show a decreasing trend but with a strong inter-annual variability. In specific areas, an increase of the wet surfaces is even observed. Ground expertise and historical knowledge of the development of the territory enable to link the decrease to ongoing excavation of drainage canals and the increase of deforestation and land reclamation, exposing flooded surfaces previously hidden by vegetation cover. By contrast, in Vietnam, the decreasing trend in wet surfaces is very clear and can be explained by the development of dykes dating back to the 1990s with an acceleration in the late 2000s as part of a national strategy of agriculture intensification. This study shows that coupling satellite data with ground-expertise allows to monitor surface waters at mesoscale (2), demonstrating the potential of interdisciplinary approaches for water ressource management and planning.

Published
2020
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13. A Bibliometric and Content Analysis of Articles in Remote Sensing From Vietnam Indexed in Scopus for the 2000–2019 Period

Author

Binh Pham-Duc, Tran Trung, Cuong Le Minh, Ho Nguyen, and Linh Hoang Khanh

Subjects
Bibliometric analysis, Vietnamese, 05 social sciences, Scopus, Library and Information Sciences, 050905 science studies, language.human_language, Geography, Content analysis, Remote sensing (archaeology), language, 0509 other social sciences, 050904 information & library sciences, Remote sensing
Abstract

In this study, a bibliometric analysis is conducted to evaluate bibliographic content of all scientific publications in the field of remote sensing published by scholars with Vietnamese affiliation...

Published
2020
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14. Global scientific literature on human resource development: a bibliometric analysis using Scopus database

Author

Binh Pham-Duc, Trung Tran, Dung Huu Hoang, and Chau Bao Do

Subjects
Organizational Behavior and Human Resource Management
Abstract

Purpose This paper aims to analyze the development of global human resource development (HRD) articles published in journals indexed in the Scopus database since 1960s until present time. Design/methodology/approach A publication collection of 1,905 articles collected from the Scopus database was downloaded and analyzed by using bibliometric techniques available in the VOSviewer and Biblioshiny software. Findings Three different development stages of HRD research have been identified: a seeding stage between 1962 and 1989, a growth stage between 1990 and 2007 and a development stage from 2008 onward. The USA and the UK were the biggest contributors who participated to 30.02% and 12.55% of articles in the collection and received 43.82% and 19.54% of the total number of citations, respectively. Scholars with the most publications and citations are mostly from the USA and the UK, and nine over ten most cited articles having first author’s affiliation located there. Emerald Group is the most popular publishing house, as five over ten most popular journals belong to this publishing house. Originality/value After six decades of development, it is necessary to examine the evolution of HRD research, its characteristics and its intellectual framework as this type of analysis is not yet available in the literature. This study helps scholars better understand this research field, as well as better prepare for future work in HRD.

Published
2022
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15. A bibliometric analysis on the visibility of the Sentinel-1 mission in the scientific literature

Author

Binh Pham-Duc and Ho Nguyen

Subjects
General Earth and Planetary Sciences, General Environmental Science
Abstract

Seven years after the launch of the first Sentinel-1 satellite, its data have been widely used in the scientific community. This study provides the first quantitative analysis of the visibility of the Sentinel-1 mission to the scientific literature through a bibliometric analysis of 1628 articles published in scientific journals during the 2014–2020 period. The main findings show that the number of Sentinel-1 mission-related papers increased significantly over the years, with an annual growth rate of 83%. Remote sensing is the most popular journal where 31.75% of the publication collection has been published. China and the USA are the two most productive countries with a share of 22.30% and 16.22% in the collection. Research based on the Sentinel-1 data covered a wide range of topics in geoscience disciplines. The use of SAR interferometry, focusing on the studies of landslide, earthquake, ground deformation, and subsidence, is the most important research direction using Sentinel-1 data. Image fusion of Sentinel-1 and Sentinel-2 observations for mapping and monitoring applications is the second most important research direction. Other popular research areas are glaciology, soil moisture, agriculture, rice monitoring, and ship detection. This study uses bibliographic data derived only from the Scopus database; therefore, it might not cover all Sentinel-1 related documents. However, this paper is a good reference for researchers who want to use Sentinel-1 data in their studies. The two Sentinel-1 satellites will provide scientific data for years to come, meaning that this type of analysis should be done on a regular basis.

Published
2022
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16. Monitoring spatial-temporal dynamics of small lakes based on SAR Sentinel-1 observations: a case study over Nui Coc Lake (Vietnam)

Author

Binh Pham Duc and Son Tong Si

Subjects
Oceanography, General Earth and Planetary Sciences, Environmental science
Abstract

For the first time, this study estimates the variation of surface water extent of Nui Coc Lake located in Thai Nguyen province in North Vietnam at high spatial (20 m) and temporal resolution (bi-weekly). The classification methodology was developed based on the use of the Otsu threshold algorithm on the histogram of the backscatter coefficient of the SAR Sentinel-1 signal. Totally, more than 150 SAR Sentinel-1 images have been processed for the 2016-2020 period. Except for extreme drought and flood conditions, the average minimum and maximum of the lake’s surface water extent are 17 km2 (in May) and 24 km2 (in September/October), respectively, and Nui Coc Lake’s surface water was stable during the last five years. Classification results are in good agreement with the corresponding surface water extent maps derived from free-cloud Sentinel-2 images, with the occurrence map derived from the Landsat-derived Global Surface Water (GSW) product, and with in situ precipitation data. Compared to Sentinel-2, the lake’s surface water extent detected from Sentinel-1 is 4-4.5% less. The water occurrence is similar between our results and that derived from the GSW product, but Sentinel-1 data provide more details as its spatial resolution is higher than Landsat. This study clearly shows the great potential of SAR Sentinel-1 data for monitoring small lake’s water surface at low costs, especially over tropical regions.

Published
2021
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17. Lake Chad hydrological cycle under current climate change

Author

Frédéric Frappart, Abdallah Mahamat Nour, Muriel Berge-Nguyen, Binh Pham Duc, Florence Sylvestre, Camille Bouchez, Jean-François Crétaux, Fabrice Papa, Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of N'Djamena, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), 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 de Recherche pour le Développement (IRD)-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), Hanoi University of Science and Technology (HUST), Géosciences Rennes (GR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), European Geosciences Union, 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)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS)

Subjects
2. Zero hunger, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Climate change, Environmental science, 15. Life on land, Current (fluid), Water cycle, 6. Clean water
Abstract

In a near future, the Sahara and Sahelian regions could experience more rainfall than today as a result of climate change. Wetter conditions in the hottest and driest place of the planet today raise the question of whether the near future might hold in store environmental transformations, particularly in view of the growing human-induced climate, land-use and land-cover changes. Reflecting an enhancement of the global hydrological cycle under warmer conditions, some experiments provide support for the notion of a strengthening of the monsoon in the future and more rainfall in central Sahel and Sahara. However, some remote forcing could counterbalance the decadal trend. Modeling experiments suggest that the freshwater discharge coming from Greenland melting could significantly impact the sea surface temperature of North Atlantic and induce a decrease in Sahel rainfall for the next decades, remaining left open the question how Sahara will be in a warmer climate?By chance, Lake Chad, located at the southern edge of the Sahara, is recognized for being the best site in Africa for deciphering hydrological and climate change. After being ranked at the world’s sixth largest inland water body with an open water area of 25,000 km2 in the 1960s, it shrunk dramatically at the beginning of the 1970s and reached less than 2000 km2 during the 1980s, decreasing by more 90% in area. Because it provides food and water to 50 millions of people, it becomes crucial to observe precisely its hydrological cycle during the last 20 years.Here by using a new multi-satellite approach combined with ground-based observations, we show that Lake Chad extent has remained stable during the last two decades, slightly increasing at 14,000 km2. We extend further this reconstruction by adding new data from the hydrological year 2019-2020, which is considered at an extreme in precipitation recorded over the Sahel. Moreover, since the 2000s, groundwater which contributes to 70% of Lake Chad’s annual water storage, is increasing due to water supply provide by its two main tributaries draining a catchment area 610,000 km2 wide. Because the current climate change seems to be characterize by a higher interannual variability affecting from year to year the amount of precipitation during the rainy season and increasing the vulnerability of the economy of the region mainly based of agropastoral activities, we investigate the yearly cycle and see how it is impacted the hydrological cycle of Lake Chad and changed over time.

Published
2021
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18. The Lake Chad hydrology under current climate change

Author

Frédéric Frappart, Florence Sylvestre, Binh Pham-Duc, Camille Bouchez, Jean-François Crétaux, Fabrice Papa, Hanoi University of Science and Technology (HUST), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National d'Etudes Spatiales - Direction Des Lanceurs. (CNES), University of Brasilia [Brazil] (UnB), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), 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 de Recherche pour le Développement (IRD)-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), Géosciences Rennes (GR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), United Nations Development Programme (UNDP), Adelphi (Berlin), Federal Foreign Office of Germany, Ministry of Foreign Affairs of the Kingdom of the Netherlands, French National Research Institute for Sustainable Development (IRD, France), Centre National d'Etudes Spatiales (CNES) through the TOSCA project, Adelphi, 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)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)

Subjects
010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, Biodiversity, lcsh:Medicine, Water supply, Climate change, 02 engineering and technology, 01 natural sciences, Article, Hydrology (agriculture), Tributary, Precipitation, lcsh:Science, 0105 earth and related environmental sciences, 2. Zero hunger, Hydrology, Multidisciplinary, geography.geographical_feature_category, business.industry, lcsh:R, Water storage, 15. Life on land, 6. Clean water, 020801 environmental engineering, Environmental sciences, Geography, [SDU]Sciences of the Universe [physics], 13. Climate action, lcsh:Q, business, Surface water
Abstract

Lake Chad, in the Sahelian zone of west-central Africa, provides food and water to ~50 million people and supports unique ecosystems and biodiversity. In the past decades, it became a symbol of current climate change, held up by its dramatic shrinkage in the 1980s. Despites a partial recovery in response to increased Sahelian precipitation in the 1990s, Lake Chad is still facing major threats and its contemporary variability under climate change remains highly uncertain. Here, using a new multi-satellite approach, we show that Lake Chad extent has remained stable during the last two decades, despite a slight decrease of its northern pool. Moreover, since the 2000s, groundwater, which contributes to ~70% of Lake Chad’s annual water storage change, is increasing due to water supply provided by its two main tributaries. Our results indicate that in tandem with groundwater and tropical origin of water supply, over the last two decades, Lake Chad is not shrinking and recovers seasonally its surface water extent and volume. This study provides a robust regional understanding of current hydrology and changes in the Lake Chad region, giving a basis for developing future climate adaptation strategies.

Published
2020
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19. Variations of surface and subsurface water storage in the lower Mekong Basin (Vietnam and Cambodia) from multisatellite observations

Author

Fabrice Papa, Binh Pham-Duc, Filipe Aires, Catherine Prigent, Frédéric Frappart, Sylvain Biancamaria, Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA (UMR_8112)), Sorbonne Université (SU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Vietnam Academy of Science and Technology (VAST), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Collège de France (CdF (institution))-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Collège de France (CdF (institution))-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-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)-Centre National de la Recherche Scientifique (CNRS), Indo-French Cell for Water Sciences (IFCWS), Indian Institute of Science [Bangalore] (IISc Bangalore), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), 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 de Recherche pour le Développement (IRD)-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), PSL Research University (PSL)-PSL Research University (PSL)-Université de Cergy Pontoise (UCP), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Collège de France (CdF)-Institut national des sciences de l'Univers (INSU - CNRS)-Aix Marseille Université (AMU)-Institut National de la Recherche Agronomique (INRA), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire Midi-Pyrénées (OMP), and Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)

Subjects
010504 meteorology & atmospheric sciences, Range (biology), Geography, Planning and Development, 0207 environmental engineering, surface-water extent, subsurface-water volume, 02 engineering and technology, Aquatic Science, 01 natural sciences, Biochemistry, Mekong river, surface-water volume, 14. Life underwater, Altimeter, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, 020701 environmental engineering, Subsurface flow, Water content, 0105 earth and related environmental sciences, Water Science and Technology, satellite altimetry, 6. Clean water, MODIS, 13. Climate action, Climatology, Period (geology), Environmental science, Scale (map), Lower Mekong Basin, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Groundwater
Abstract

In this study, we estimate monthly variations of surface-water storage (SWS) and subsurface water storage (SSWS, including groundwater and soil moisture) within the Lower Mekong Basin located in Vietnam and Cambodia during the 2003&ndash, 2009 period. The approach is based on the combination of multisatellite observations using surface-water extent from MODIS atmospherically corrected land-surface imagery, and water-level variations from 45 virtual stations (VS) derived from ENVISAT altimetry measurements. Surface-water extent ranges from &sim, 6500 to &sim, 40,000 km 2 during low and high water stages, respectively. Across the study area, seasonal variations of water stages range from 8 m in the upstream parts to 1 m in the downstream regions. Annual variation of SWS is &sim, 40 km 3 for the 2003&ndash, 2009 period that contributes to 40&ndash, 45% of total water-storage (TWS) variations derived from Gravity Recovery And Climate Experiment (GRACE) data. By removing the variations of SWS from GRACE-derived TWS, we can isolate the monthly variations of SSWS, and estimate its mean annual variations of &sim, 50 km 3 (55&ndash, 60% of the TWS). This study highlights the ability to combine multisatellite observations to monitor land-water storage and the variations of its different components at regional scale. The results of this study represent important information to improve the overall quality of regional hydrological models and to assess the impacts of human activities on the hydrological cycles.

Published
2019
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20. Comparisons of Global Terrestrial Surface Water Datasets over 15 Years

Author

Filipe Aires, Binh Pham-Duc, Catherine Prigent, Fabrice Papa, Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), 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 de Recherche pour le Développement (IRD)-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)

Subjects
Hydrology, Atmospheric Science, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, 0208 environmental biotechnology, Wetland, 02 engineering and technology, 01 natural sciences, Swamp, 020801 environmental engineering, Period (geology), Environmental science, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Seasonal cycle, Surface water, 0105 earth and related environmental sciences
Abstract

Continental surface water extents and dynamics are key information to model Earth’s hydrological and biochemical cycles. This study presents global and regional comparisons between two multisatellite surface water extent datasets, the Global Inundation Extent from Multi-Satellites (GIEMS) and the Surface Water Microwave Product Series (SWAMPS), for the 1993–2007 period, along with two widely used static inundation datasets, the Global Lakes and Wetlands Database (GLWD) and the Matthews and Fung wetland estimates. Maximum surface water extents derived from these datasets are largely different: ~13 × 106 km2 from GLWD, ~5.3 × 106 km2 from Matthews and Fung, ~6.2 × 106 km2 from GIEMS, and ~10.3 × 106 km2 from SWAMPS. SWAMPS global maximum surface extent reduces by nearly 51% (to ~5 × 106 km2) when applying a coastal filter, showing a strong contamination in this retrieval over the coastal regions. Anomalous surface waters are also detected with SWAMPS over desert areas. The seasonal amplitude of the GIEMS surface waters is much larger than the SWAMPS estimates, and GIEMS dynamics is more consistent with other hydrological variables such as the river discharge. Over the Amazon basin, GIEMS and SWAMPS show a very high time series correlation (95%), but with SWAMPS maximum extent half the size of that from GIEMS and from previous synthetic aperture radar estimates. Over the Niger basin, SWAMPS seasonal cycle is out of phase with both GIEMS and MODIS-derived water extent estimates, as well as with river discharge data.

Published
2017
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21. Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations

Author

Filipe Aires, Catherine Prigent, Binh Pham-Duc, Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université de Cergy Pontoise (UCP), and Université Paris-Seine-Université Paris-Seine-Centre National de la Recherche Scientifique (CNRS)

Subjects
Synthetic aperture radar, 010504 meteorology & atmospheric sciences, Cloud cover, Geography, Planning and Development, 0211 other engineering and technologies, 02 engineering and technology, Aquatic Science, Temporal correlation, 01 natural sciences, Biochemistry, Dry season, High spatial resolution, Environmental science, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], SAR, Sentinel-1, surface water monitoring, neural network, Mekong Delta, Landsat-8, MODIS, Mekong delta, Surface water, Image resolution, 021101 geological & geomatics engineering, 0105 earth and related environmental sciences, Water Science and Technology, Remote sensing
Abstract

This study presents a methodology to detect and monitor surface water with Sentinel-1 Synthetic Aperture Radar (SAR) data within Cambodia and the Vietnamese Mekong Delta. It is based on a neural network classification trained on Landsat-8 optical data. Sensitivity tests are carried out to optimize the performance of the classification and assess the retrieval accuracy. Predicted SAR surface water maps are compared to reference Landsat-8 surface water maps, showing a true positive water detection of ∼90% at 30 m spatial resolution. Predicted SAR surface water maps are also compared to floodability maps derived from high spatial resolution topography data. Results show high consistency between the two independent maps with 98% of SAR-derived surface water located in areas with a high probability of inundation. Finally, all available Sentinel-1 SAR observations over the Mekong Delta in 2015 are processed and the derived surface water maps are compared to corresponding MODIS/Terra-derived surface water maps at 500 m spatial resolution. Temporal correlation between these two products is very high (99%) with very close water surface extents during the dry season when cloud contamination is low. This study highlights the applicability of the Sentinel-1 SAR data for surface water monitoring, especially in a tropical region where cloud cover can be very high during the rainy seasons.

Published
2017
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22. Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations.

Author

Binh Pham-Duc, Prigent, Catherine, and Aires, Filipe

Subjects
WATER & the environment, ENVIRONMENTAL mapping, AERIAL surveys, SYNTHETIC aperture radar, FLOOD risk
Abstract

This study presents a methodology to detect and monitor surface water with Sentinel-1 Synthetic Aperture Radar (SAR) data within Cambodia and the Vietnamese Mekong Delta. It is based on a neural network classification trained on Landsat-8 optical data. Sensitivity tests are carried out to optimize the performance of the classification and assess the retrieval accuracy. Predicted SAR surface water maps are compared to reference Landsat-8 surface water maps, showing a true positive water detection of ~90% at 30 m spatial resolution. Predicted SAR surface water maps are also compared to flood ability maps derived from high spatial resolution topography data. Results show high consistency between the two independent maps with 98% of SAR-derived surface water located in areas with a high probability of inundation. Finally, all available Sentinel-1 SAR observations over the Mekong Delta in 2015 are processed and the derived surface water maps are compared to corresponding MODIS/Terra-derived surface water maps at 500 m spatial resolution. Temporal correlation between these two products is very high (99%) with very close water surface extents during the dry season when cloud contamination is low. This study highlights the applicability of the Sentinel-1 SAR data for surface water monitoring, especially in a tropical region where cloud cover can be very high during the rainy seasons. [ABSTRACT FROM AUTHOR]

Published
2017
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