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

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 8517MODIS 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.

Monitoring Cropland Dynamics of the Yellow River Delta based on Multi-Temporal Landsat Imagery over 1986 to 2015

“…[1][2][3][4][5]. Meanwhile, the flat topography, sufficient water supply and fertile arable land have made river deltas preferential areas for human settlements and intensified agriculture practices [3][4][5], resulting in plenty of croplands co-existing with coastal wetlands.…”

“…[1][2][3][4][5]. Meanwhile, the flat topography, sufficient water supply and fertile arable land have made river deltas preferential areas for human settlements and intensified agriculture practices [3][4][5], resulting in plenty of croplands co-existing with coastal wetlands. However, due to intensive anthropogenic activities such as industrialization and urban sprawl, the croplands in natural deltas have experienced great dynamics [6][7][8][9][10], e.g., some croplands were converted to built up areas while some wetlands were reclaimed as the cultivated land in some natural deltas of China.…”

“…Considering the dynamic nature of river deltas [3][4][5], it is time-consuming and impractical to rely on traditional field surveys to monitor the land use and land cover change (LUCC). Nevertheless, satellite remote sensing has yielded promising results in mapping and monitoring river deltas due to its synoptic view, multi-temporal coverage, multi-sensor data collection and cost-effectiveness [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16].…”

“…Nevertheless, satellite remote sensing has yielded promising results in mapping and monitoring river deltas due to its synoptic view, multi-temporal coverage, multi-sensor data collection and cost-effectiveness [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The Landsat program has been considered as one of the most successful and important missions for Earth Observation in the last forty years [5].…”

Modeling 25 years of spatio-temporal surface water and inundation dynamics on large river basin scale using time series of Earth observation data

“…EO data enable analyses of changes in the availability and distribution of surface water at continental or sub-continental scales based on comparison of snapshots of the state of the system at two (Baker et al, 2007;Teferi et al, 2010) or multiple points in time (Huang et al, 2014b;Zhao et al, 2011). The opening of archives of continuous optical satellite data, such as Landsat and MODIS imagery, further increased the potential of performing time series analysis of remotely sensed surface water extent (SWE) and inundation dynamics over large areas and long periods of time (Klein et al, 2014;Kuenzer et al, 2015;Mccarthy et al, 2003;Sakamoto et al, 2007;Tulbure and Broich, 2013;Tulbure et al, 2016). Such EO-based analyses of SWE dynamics are to be distinguished from EO-based flood mapping, which focuses on flooding of areas that are not frequently inundated and large-scale damage assessment of floods .…”