基于POBI插值变化率的星载GNSS-R洪水动态监测OA

To address the issues of reduced accuracy and misidentification of single water bodies caused by interpolation in large-scale flood inundation mapping using spaceborne GNSS-R technology,this paper proposes a dynamic monitoring method based on the reflectivity change rate using period-matched observation-based interpolation(POBI).Utilizing CYGNSS reflectivity data during the rainy seasons from 2019 to 2023 and China's 1 km resolution monthly precipitation products,we construc-ted a POBI spatial interpolation model.By combining this with the bistatic radar equation to retrieve surface reflectivity,we systematically analyzed the flood evolution process during the extreme rainfall event in Guilin in June 2024.The results show that,for reflectivity interpolation in unsampled areas,the root mean square error(RMSE)decreased by an average of 20.98％compared to the natural neighbor method.The inundation identification mechanism based on the change rate effectively avoids the subjectivity of traditional threshold methods.The monitoring results indicate that the inundated area in the central urban district expanded by 48.68％from June 19 to June 12,with spatial evolution highly consistent with changes in SMAP soil moisture.This study provides reliable methodological support for refined flood monitoring in highly dynamic,low-coverage areas using spaceborne GNSS-R.