Journal
REMOTE SENSING
Volume 12, Issue 5, Pages -Publisher
MDPI
DOI: 10.3390/rs12050800
Keywords
wetlands; inundation; satellite remote sensing; trend analysis; hydrology; Vietnam; Cambodia; water control
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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 (<100 x 100 km(2)), demonstrating the potential of interdisciplinary approaches for water ressource management and planning.
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