Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series
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 r...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
MDPI AG
2015
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs70708516 https://doaj.org/article/ed60ffd25ba64f65b3d02c342baf4ddc |
_version_ | 1821578385803968512 |
---|---|
author | Claudia Kuenzer Igor Klein Tobias Ullmann Efi Foufoula Georgiou Roland Baumhauer Stefan Dech |
author_facet | Claudia Kuenzer Igor Klein Tobias Ullmann Efi Foufoula Georgiou Roland Baumhauer Stefan Dech |
author_sort | Claudia Kuenzer |
collection | Directory of Open Access Journals: DOAJ Articles |
container_issue | 7 |
container_start_page | 8516 |
container_title | Remote Sensing |
container_volume | 7 |
description | 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 ... |
format | Article in Journal/Newspaper |
genre | Mackenzie Delta Thermokarst |
genre_facet | Mackenzie Delta Thermokarst |
geographic | Canada |
geographic_facet | Canada |
id | ftdoajarticles:oai:doaj.org/article:ed60ffd25ba64f65b3d02c342baf4ddc |
institution | Open Polar |
language | English |
op_collection_id | ftdoajarticles |
op_container_end_page | 8542 |
op_doi | https://doi.org/10.3390/rs70708516 |
op_relation | http://www.mdpi.com/2072-4292/7/7/8516 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs70708516 https://doaj.org/article/ed60ffd25ba64f65b3d02c342baf4ddc |
op_source | Remote Sensing, Vol 7, Iss 7, Pp 8516-8542 (2015) |
publishDate | 2015 |
publisher | MDPI AG |
record_format | openpolar |
spelling | ftdoajarticles:oai:doaj.org/article:ed60ffd25ba64f65b3d02c342baf4ddc 2025-01-16T23:01:44+00:00 Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series Claudia Kuenzer Igor Klein Tobias Ullmann Efi Foufoula Georgiou Roland Baumhauer Stefan Dech 2015-07-01T00:00:00Z https://doi.org/10.3390/rs70708516 https://doaj.org/article/ed60ffd25ba64f65b3d02c342baf4ddc EN eng MDPI AG http://www.mdpi.com/2072-4292/7/7/8516 https://doaj.org/toc/2072-4292 2072-4292 doi:10.3390/rs70708516 https://doaj.org/article/ed60ffd25ba64f65b3d02c342baf4ddc Remote Sensing, Vol 7, Iss 7, Pp 8516-8542 (2015) remote sensing river deltas inundation flooding MODIS Yellow River Delta Mekong Delta Irrawaddy Delta Ganges-Brahmaputra Delta Mackenzie Delta Science Q article 2015 ftdoajarticles https://doi.org/10.3390/rs70708516 2022-12-31T10:19:51Z 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 ... Article in Journal/Newspaper Mackenzie Delta Thermokarst Directory of Open Access Journals: DOAJ Articles Canada Remote Sensing 7 7 8516 8542 |
spellingShingle | remote sensing river deltas inundation flooding MODIS Yellow River Delta Mekong Delta Irrawaddy Delta Ganges-Brahmaputra Delta Mackenzie Delta Science Q Claudia Kuenzer Igor Klein Tobias Ullmann Efi Foufoula Georgiou Roland Baumhauer Stefan Dech Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series |
title | Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series |
title_full | Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series |
title_fullStr | Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series |
title_full_unstemmed | Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series |
title_short | Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series |
title_sort | remote sensing of river delta inundation: exploiting the potential of coarse spatial resolution, temporally-dense modis time series |
topic | remote sensing river deltas inundation flooding MODIS Yellow River Delta Mekong Delta Irrawaddy Delta Ganges-Brahmaputra Delta Mackenzie Delta Science Q |
topic_facet | remote sensing river deltas inundation flooding MODIS Yellow River Delta Mekong Delta Irrawaddy Delta Ganges-Brahmaputra Delta Mackenzie Delta Science Q |
url | https://doi.org/10.3390/rs70708516 https://doaj.org/article/ed60ffd25ba64f65b3d02c342baf4ddc |