Source Parameter Estimation of the 2009 Ms6.0 Yao’an Earthquake, Southern China, Using InSAR Observations

Quantitatively Estimating of InSAR Decorrelation Based on Landsat-Derived NDVI

As a by-product of Interferometric Synthetic Aperture Radar (SAR, InSAR) technique, interferometric coherence is a measure of the decorrelation noise for InSAR observation, where the lower the coherence value, the more serious the decorrelation noise. In the densely vegetated area, the coherence value could be too low to obtain any valuable signals, leading to the degradation of InSAR performance and the possible waste of expensive SAR data. Normalized Difference Vegetation Index (NDVI) value is a measure of the vegetation coverage and can be estimated from the freely available optical satellite images. In this paper, a multi-stage model is established to quantitatively estimate the decorrelation noise for vegetable areas based on Landsat-derived NDVI prior to the acquisition of SAR data. The modeling process is being investigated with the L-band ALOS-1/PALSAR-1 data and the Landsat-5 optical data acquired in the Meitanba area of Hunan Province, China. Furthermore, the reliability of the established model is verified in the Longhui area, which is situated near the Meitanba area. The results demonstrate that the established model can quantitatively estimate InSAR decorrelation associated with the vegetation coverage.

Monitoring the Land Subsidence Area in a Coastal Urban Area with InSAR and GNSS

In recent years, the enormous losses caused by urban surface deformation have received more and more attention. Traditional geodetic techniques are point-based measurements, which have limitations in using traditional geodetic techniques to detect and monitor in areas where geological disasters occur. Therefore, we chose Interferometric Synthetic Aperture Radar (InSAR) technology to study the surface deformation in urban areas. In this research, we discovered the land subsidence phenomenon using InSAR and Global Navigation Satellite System (GNSS) technology. Two different kinds of time-series InSAR (TS-InSAR) methods: Small BAseline Subset (SBAS) and the Permanent Scatterer InSAR (PSI) process were executed on a dataset with 31 Sentinel-1A Synthetic Aperture Radar (SAR) images. We generated the surface deformation field of Shenzhen, China and Hong Kong Special Administrative Region (HKSAR). The time series of the 3d variation of the reference station network located in the HKSAR was generated at the same time. We compare the characteristics and advantages of PSI, SBAS, and GNSS in the study area. We mainly focus on the variety along the coastline area. From the results generated by SBAS and PSI techniques, we discovered the occurrence of significant subsidence phenomenon in the land reclamation area, especially in the metro construction area and the buildings with a shallow foundation located in the land reclamation area.