Affiliation:
1. Lanzhou Jiaotong University
Abstract
To monitor the ground sink condition of Shanghai over the past two
years, monitoring data were obtained through the technical processing of
24 views from Sentinel-1A data covering Shanghai from 2019–2020 by
using the PS-InSAR and SBAS-InSAR technique. The ground subsidence
results were extracted via PS interferometry processing, while SRTM data
were used to correct the residual phase. The subsidence rate and the
accumulated amount of subsidence derived from the monitoring results
revealed the urban area in Shanghai to be principally characterized by
uneven ground subsidence, with multiple settlement funnels being found
to be distributed across the main urban area. Moreover, when compared
with the historical subsidence data, geological data, and urban
construction distribution data, the individual settlement funnels were
observed to correspond to those data concerning the historical surface
settlement funnel in Shanghai. By randomly selecting ground subsidence
time-series data regarding three feature points, it was determined that
the morphological variables of the ground subsidence remained largely
consistent at all time points and that their change trends exhibited a
high degree of consistency, which verified the reliability of the
PS-InSAR and SBAS-InSAR monitoring method. The results can provide data
support for decision making in terms of geological disaster prevention
and control in Shanghai.
Cited by
1 articles.
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