This dataset contains vertical displacement times series of the Earth’s surface in the Vietnamese Mekong Delta for the time period between April 2017 and April 2022, which were estimated with the Persistent Scatterer Interferometry (PSI) method described in Dörr et al. (2024, accepted for publication). The method was applied to descending and ascending SAR stacks acquired by ESA’s Sentinel-1 constellation, which contained 277 and 115 VV-polarized SAR scenes, respectively, and were acquired in the interferometric wide swath mode. The applied PSI method features (i) a full integration of Temporary Persistent Scatterers, enabling the monitoring of areas with infrastructural land cover changes during the considered time series; (ii) a method to optimally integrated reference points with known displacement to suppress spatially correlated noise. For the latter, we here made use of a combination of solid rock outcrops and an infrastructural reference network consisting of large bridges with deep pile foundations of about 70 m, which were selected in statistical cross-checks. Referencing to these bridges results in the fact that only subsidence originating from soil layers above their foundation depth of the used bridges could be measured in large parts of the study area. However, we discussed in Dörr et al. (2024, accepted for publication) that the largest part of the total subsidence originates from shallower layers. The provided dataset can make a crucial contribution to in-depth studies of the causes and future projections of land subsidence in the Mekong Delta. They can, for example, serve as input for hydro-geological modeling, or can be examined with regard to correlations with environmental and anthropogenic parameters, such as groundwater extraction rates, land cover and land use, as well as climatological data.
Reference: Dörr, N., Schenk, A., Hinz, S. (2024, accepted for publication). Land subsidence in the Mekong Delta Derived from Advanced Persistent Scatterer Interferometry with an Infrastructural Reference Network, accepted for publication in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.