Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series
Remote Sensing of River Delta Inundation: Exploiting the Potential of Coarse Spatial Resolution, Temporally-Dense MODIS Time Series
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DOI：
10.3390/rs70708516
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发表时间：
2015-07-01
期刊：
影响因子：
5
通讯作者：
Dech, Stefan
中科院分区：
文献类型：
--
作者：
Kuenzer, Claudia;Klein, Igor;Dech, Stefan
河流三角洲属于地球上人口密度最大的地方。尽管它们只占全球陆地表面的5%，但超过5.5亿人生活在三角洲地区。然而，这些首选的生计地点具有平坦的地形、肥沃的冲积土壤、获得河流和海洋资源、丰富的湿地生物多样性和其他优势，但受到许多内部和外部过程的威胁。社会经济发展、城市化、气候变化导致海平面上升，以及上游引水引起的洪水脉冲变化，都导致了这些高度动态的系统的变化。因此，彻底了解河流三角洲的一般情况以及年度内和长期动态，对于明智地管理自然资源至关重要。在这里，遥感可以在全球范围内分析和监测这些广袤的地区发挥关键作用。这项研究的目的是展示在时间密集但空间分辨率较低的年度内时间序列分析在描述位于四个不同国家的五个河流三角洲的洪水特征方面的潜力。基于250m的MODIS反射率数据，我们分析了四个亚洲人口稠密的河流三角洲--即黄河三角洲(中国)、湄公河三角洲(越南)、伊洛瓦底江三角洲(缅甸)和恒河-雅鲁藏布江(孟加拉国、印度)--以及一个非常反差的三角洲：加拿大西北部几乎无人居住的极地麦肯齐三角洲地区(2013年)的洪水动态。一个复杂的每日水面推算处理链允许生成年内时间序列，表明每个三角洲的淹没持续时间。我们的分析描绘了每个三角洲内不同的淹没模式，这可以归因于陆上洪水、灌溉农业、水产养殖或融雪和热岩溶过程。阐明了中纬度三角洲、副热带三角洲和极地三角洲的明显区别，并讨论了该方法用于洪水计算的优点和局限性。
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.