POBI interpolation algorithm for CYGNSS near real time flood detection research: A case study of extreme precipitation events in Henan,China in 2021

In late 2016, NASA launched the first constellation of the global navigation satellite system reflectometry (GNSS-R) small satellites called the Cyclone Global Navigation Satellite System (CYGNSS). The stable data quality and continuous free availability of CYGNSS scientific data provided a new method for flood monitoring. However, owing to the pseudorandom distribution of CYGNSS data, researchers must always choose between high temporal resolution and high spatial resolution during the performance of flood monitoring based on CYGNSS data. For floods caused by extreme precipitation with sudden and short durations, the current flood mapping based on CYGNSS data cannot be updated in near real time. However, the near real time update of the flood distribution range is meaningful for postdisaster emergency response and rapid rescue. This study aimed to address this problem using a newly proposed spatial interpolation method based on previously observed behaviour (POBI). First, a method for calculating the surface reflectivity of the CYGNSS was introduced, followed by the principle of the POBI spatial interpolation method. The applicability of the POBI method in Henan Province, China, was then analysed, and by using the flood in Henan Province, China, in July 2021 as an example, the feasibility of CYGNSS near real time flood mapping based on the POBI method was evaluated. Based on the results, near real time and 3 km flood distribution monitoring results can be obtained using the proposed new method. The results were evaluated using MODIS (Moderate Resolution Imaging Spectroradiometer) images and compared with the observations of SMAP (Soil Moisture Active Passive) and GPM (Global Precipitation Measurement) in the same period. The results show that the flooded areas obtained by CYGNSS correspond to the inundated areas in MODIS images and are also in high agreement with the SMAP. In addition, CYGNSS allows for finer mapping and quantification of inundation areas and flood duration. Moreover, we also discussed the potential of CYGNSS to detect floods in shorter periods of time (a few hours) and did a preliminary evaluation using precipitation data from meteorological stations. The results are also highly consistent.     

不同尺度范围的监测网对星基增强服务性能的影响分析

区域监测站提供的星基增强完好性监测服务在民用航空等生命安全领域发挥着重要作用。为了分析利用不同尺度监测网估计的完好性信息对用户服务性能影响,使用等效钟差方法分别实现三种不同尺度的监测网完好性参数估计,并进行增强定位验证。从增强卫星数目、用户测距误差、定位精度和保护级包络特性方面研究不同尺度的监测网对用户服务性能评估的影响,结果表明:与小尺度和中等尺度区域相比,大尺度区域增强卫星数目分别增加了50.7%、33.7%。与广播星历伪距单点定位相比,基于小、中等和大尺度区域监测网估计的改正数增强定位在水平方向定位精度分别提升了33.08%、33.59%和32.54%,垂直方向定位精度分别提升了36.56%、41.07%和43.86%。三种尺度估计的平均用户测距误差均优于0.3 m,保护级水平对定位误差的包络均能达到95%。研究成果可为区域星基增强监测网的选择提供理论支撑和应用依据。