Subsidence detection in southwest Guangdong–Hong Kong–Macao Greater Bay Area using InSAR with GNSS corrected tropospheric delays

As one of the biggest bay areas in the world, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is subject to subsidence due to thick sedimentary. In this study, we combine 154 Sentinel-1 A/B images acquired between 2017 and 2022 with Global Navigation Satellite System (GNSS) observations to characterize the subsidence in southwestern GBA. Specifically, we use GNSS to establish the Iterative Tropospheric Decomposition (ITD) model for zenith tropospheric delay correction and the model is improved using random forest algorithm to alleviate errors caused by unreasonable interpolation methods, showing better performance than Generic Tropospheric Correction Online Service (GACOS) product. At GNSS stations with complete data, the improved model utilizing GNSS data achieves a Pearson correlation coefficient of 0.659, in contrast to a coefficient of only 0.434 using GACOS. The maximum subsidence rate detected is up to 11.32 cm/year in Zhuhai, accompanied by noticeable seasonal variations correlated with precipitation. In addition to the sediment consolidation and compaction, human activities such as agriculture, construction, and land reclamation further exacerbate subsidence in the GBA. This study enhances the utility of GNSS in improving tropospheric delay correction performance and providing more accurate observations of subsidence.