CYGNSS High Spatiotemporal Resolution Flood Monitoring Based on POBI Interpolation: A Case Study of 2022 Pakistan Catastrophic Floods

Global Navigation Satellite System Reflectometry (GNSS-R) technology is gaining more and more attention from the scientific community due to its advantages of being all-weather, unaffected by clouds and rainfall, and low cost. The Cyclone Global Navigation Satellite System (CYGNSS), NASA’s first constellation of small satellites with space borne GNSS-R, was launched in late 2016, and CYGNSS data has now been shown to be useful for flood detection, in addition to the designed mission of inversion of sea surface wind fields. However, the quasi-random sampling of the surface by the CYGNSS constellation limits its potential for flood detection. Spatial interpolation techniques can bridge this gap and provide a complete coverage of high-resolution daily flood monitoring. In this paper we first introduce the CYGNSS surface reflectivity (SR) calculation method, secondly introduce a new spatial interpolation method (POBI) based on the interpolation of previously observed behavior and finally analyses the performance of CYGNSS high-resolution flood monitoring based on POBI using the 2022 Pakistan catastrophic floods as an example. The results show that compared with the common spatial interpolation methods, the CYGNSS observations based on the POBI method can not only obtain high-resolution flood monitoring results (daily, 3km), but also preserve the surface heterogeneity and discontinuity much better. The comparison with flood monitoring results obtained using microwave remote sensing data also demonstrates the feasibility of CYGNSS high spatial and temporal resolution flood monitoring based on POBI interpolation.