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Dynamic monitoring on flooding situation in the Middle and Lower Reaches of the Yangtze River Region using Sentinel-1A time series

  • role： First author第一作者
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

  • Email：gsc@smail.nju.edu.cn
  • Introduction：郭山川，1992年生，男，博士研究生，研究方向为时序SAR影像处理与分析。E-mail： gsc@smail.nju.edu.cn
GUO Shanchuan123,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

  • Email：dupjrs@126.com
  • Introduction：杜培军，1975年生，男，教授，研究方向为城市环境遥感。E-mail： dupjrs@126.com
DU Peijun123*,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

MENG Yaping123,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

WANG Xin123,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

TANG Pengfei123,  
  • Affiliation：

    School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China

    Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

    Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, Nanjing 210023, China

LIN Cong123,  
  • Affiliation：

    Geoinformatics Unit, RIKEN Center for Advanced Intelligence Project (AIP), Tokyo 103-0027, Japan

XIA Junshi4

résumé

Synthetic Aperture Radar (SAR) is an indispensable data source for the dynamic monitoring of flood events due to the capacity for all-weather and all-time sensing. At present, flooding mapping and damaging assessment are developed rapidly towards dynamic monitoring and large scale, owing to the emergence of cloud computing platforms, such as Google Earth Engine (GEE) and accessibility of short-revisit Sentinel-1A radar data. A novel method is proposed for detecting flood events and continuous monitoring of the inundated areas at a large scale based on the time-series processing and analysis from Sentinel-1A images, considering the complexity of land cover changes within the flooded areas and the temporal uncertainty of flood events. First, the binary segmentation threshold for the water extraction was determined by the maximum interclass variance algorithm, and accordingly, the coarse maps of spatiotemporal distribution of water body were generated from Sentinel-1A time series. Second, the frequency of candidate water pixels was computed through these coarse maps. The initial fine water map in the temporal sequence was refined by the water map retrieved by the NDWI from the Sentinel-2 optical image. In view of the distinctive inundation characteristics of different frequency areas, a differentiated sequential anomaly detection strategy was proposed to identify the flooded areas and the seasonal water areas. The change feature maps of backscattering coefficient were established by the Sentinel-1A time series. Euclidean distance was used to detect the sequential breakpoint in low-frequency water-covered area, which is regarded as the flooding disaster area with high disturbance intensity and short flooding time. Temporal Z-score was introduced to detect the breakpoint in high-frequency water-covered area, which is considered the continuous inundating area.Result We automatically, rapidly, and effectively detected the flood events in the middle and lower reaches of the Yangtze River Region between May and October in 2020 and monitored the inundated area change during flooding, using the proposed method deployed on the GEE. The results exhibited that the flooding areas, such as the middle reaches of the Huaihe River, the lower reaches of the Xinyi River, and the Chaohu Lake Basin, and displayed the max extents of seasonal water, such as Poyang Lake, Dongting Lake, and Shijiu Lake during extreme weather with serious precipitation. The storage, diversion, and release of the flood water in the Yangtze River Plain demonstrated a lower loss manner due to the function of the free Yangtze-linking lakes, such as Poyang Lake and Dongting Lake. In the Huaihe River Basin, the extreme rainy weather is more likely to result in flood disasters and causes public damage. The flood processing in the rainy season was described in a spatial fashion, and the regional differentiation of inundation patterns was revealed through the spatiotemporal information of the middle and lower reaches of the Yangtze River Region. The proposed rapid and robust flood monitoring method is greatly practical and important to the dynamic monitoring of flood situation, quantitative assessment of flood disaster, and rapid early warning response.

mots-clés

flooding monitoring;water mapping;SAR time series;Google Earth Engine;Middle and Lower Reaches of the Yangtze River Region;Sentinel-1A

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