Abstract
NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( T b C ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology.
Highlights
Natural disasters occur frequently in China due to its complex geographic environment
The results show the capability of Cyclone Global Navigation Satellite System (CYGNSS) for both monitoring flood inundation dynamics and acquiring flood inundation areas
To evaluate the influence of the entire typhoon season, a non-typhoon season, i.e., DOY 99–150 was defined with the same interval of time as the typhoon season, starting from the available date of the CYGNSS data
Summary
Natural disasters occur frequently in China due to its complex geographic environment. Typhoons and extreme precipitation are two kinds of primary natural disasters, occurring in southeast China along the coast and middle and lower Yangtze River [1]. Flood disaster risks induced by flooding events have been causing increasing concerns due to the dense population and highly developed economies in these regions [2]. The timely and accurate mapping of the areas most impacted by flooding events can reinforce the capacity building of emergency response teams when disasters occur. Satellite remote sensing is an effective approach to mapping flooded regions [3]. Optical remote sensing (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat) does not work during flood events due to the influence of clouds and rain. In contrast, is not affected by severe weather. Microwave observations are either at coarse spatial resolutions (10–70 km for passive sensors, e.g., Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), Scanning Multi-channel Microwave Radiometer (SMMR) and Advanced Microwave
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