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Remote Sens. 2015, 7(7), 8516-8542; doi:10.3390/rs70708516

Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series

1
German Remote Sensing Data Centre, DFD, German Earth Observation Center, EOC, of the German Aerospace Centre, DLR, Oberpfaffenhofen, D-82234 Wessling, Germany
2
Department of Geography and Geology, University of Wuerzburg, Am Hubland, D-97074 Wuerzburg, Germany
3
Department of Civil Engineering, University of Minnesota, Twin Cities, St. Anthony Falls Laboratory & National Center for Earth-surface Dynamics (NCED), 2 Third Avenue SE, Minneapolis, MN 55414, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Deepak R. Mishra and Prasad S. Thenkabail
Received: 9 April 2015 / Revised: 8 June 2015 / Accepted: 17 June 2015 / Published: 6 July 2015
View Full-Text   |   Download PDF [26465 KB, uploaded 6 July 2015]   |  

Abstract

River deltas belong to the most densely settled places on earth. Although they only account for 5% of the global land surface, over 550 million people live in deltas. These preferred livelihood locations, which feature flat terrain, fertile alluvial soils, access to fluvial and marine resources, a rich wetland biodiversity and other advantages are, however, threatened by numerous internal and external processes. Socio-economic development, urbanization, climate change induced sea level rise, as well as flood pulse changes due to upstream water diversion all lead to changes in these highly dynamic systems. A thorough understanding of a river delta’s general setting and intra-annual as well as long-term dynamic is therefore crucial for an informed management of natural resources. Here, remote sensing can play a key role in analyzing and monitoring these vast areas at a global scale. The goal of this study is to demonstrate the potential of intra-annual time series analyses at dense temporal, but coarse spatial resolution for inundation characterization in five river deltas located in four different countries. Based on 250 m MODIS reflectance data we analyze inundation dynamics in four densely populated Asian river deltas—namely the Yellow River Delta (China), the Mekong Delta (Vietnam), the Irrawaddy Delta (Myanmar), and the Ganges-Brahmaputra (Bangladesh, India)—as well as one very contrasting delta: the nearly uninhabited polar Mackenzie Delta Region in northwestern Canada for the complete time span of one year (2013). A complex processing chain of water surface derivation on a daily basis allows the generation of intra-annual time series, which indicate inundation duration in each of the deltas. Our analyses depict distinct inundation patterns within each of the deltas, which can be attributed to processes such as overland flooding, irrigation agriculture, aquaculture, or snowmelt and thermokarst processes. Clear differences between mid-latitude, subtropical, and polar deltas are illustrated, and the advantages and limitations of the approach for inundation derivation are discussed. View Full-Text
Keywords: remote sensing; river deltas; inundation; flooding; MODIS; Yellow River Delta; Mekong Delta; Irrawaddy Delta; Ganges-Brahmaputra Delta; Mackenzie Delta remote sensing; river deltas; inundation; flooding; MODIS; Yellow River Delta; Mekong Delta; Irrawaddy Delta; Ganges-Brahmaputra Delta; Mackenzie Delta
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kuenzer, C.; Klein, I.; Ullmann, T.; Georgiou, E.F.; Baumhauer, R.; Dech, S. Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series. Remote Sens. 2015, 7, 8516-8542.

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