Abstract
This work investigated the large-scale ground deformations threatening the Northern Urumqi district, China, which are connected to groundwater exploitation and the seasonal freeze–thaw cycles that characterize this frozen region. Ground deformations can be well captured by satellite data using a multi-temporal interferometric synthetic aperture radar (Mt-InSAR) approach. The accuracy of the achievable ground deformation products (e.g., mean displacement time series and related ground displacement time series) critically depends on the number and quality of the selected interferograms. This paper presents a straightforward interferogram selection algorithm that can be applied to identify an optimal network of small baseline (SB) interferograms. The selected SB interferograms are then used to produce ground deformation products using the well-known small baseline subset (SBAS) Mt-InSAR algorithm. The developed interferogram selection algorithm (ISA) permits the selection of the group of SB data pairs that minimize the relative error of the mean ground deformation velocity. Experiments were carried out using a group of 102 Sentinel-1B SAR data collected from 12 April 2017 to 29 October 2020. This research study shows that the investigated farmland region is characterized by a maximum ground deformation rate of about 120 mm/year. Periodic groundwater overexploitation, coupled with irrigation and freeze–thaw phases, is also responsible for seasonal (one-year) ground displacement signals, with oscillation amplitudes up to 120 mm in the zones of maximum displacement.
Highlights
The study of the Earth’s surface displacements through differential SAR interferometry represents a consolidated practice [1,2,3,4] at present
We present a new method for selecting a suitable set of small baseline (SB) interferometric SAR data pairs to be used by the small baseline subset (SBAS) algorithm
We propose a novel strategy for selecting an adjusted network of SB
Summary
The study of the Earth’s surface displacements through differential SAR interferometry represents a consolidated practice [1,2,3,4] at present. They can be broadly grouped into two main categories: persistent scatterer (PS) and small baseline (SB) methodologies The former contains algorithms and tools based on the analysis of pointwise, highly reflective objects (e.g., human-made infrastructures in urban areas) that preserve high coherence and phase stability even in large temporal and perpendicular baseline SAR data pairs. The techniques in the latter category are primarily devoted to analyzing ground displacement related to distributed scatterers (DSs) on the terrain.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
