Using Multisensor SAR Datasets to Monitor Land Subsidence in Los Angeles from 2003 to 2017

Joint Authors

Hu, Bo
Zhang, Xingfu
Chen, Xiongle

Source

Journal of Sensors

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-15, 15 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-02-27

Country of Publication

Egypt

No. of Pages

15

Main Subjects

Civil Engineering

Abstract EN

Los Angeles has undergone tremendous deformations over the past few decades, mainly due to human factors such as natural disasters and earthquakes, urban construction, overexploitation of groundwater, and oil extraction.

The purpose of this study is to map the temporal and spatial variations of land subsidence in Los Angeles and to use the improved SBAS (small baseline subset) technique and multisensor SAR datasets to analyze the causes of deformations in this area from October 2003 to October 2017.

At the same time, the deformation results of SBAS inversion are compared with the GPS measurements and the multisensor SAR dataset deformation, and the results are highly consistent.

During the period from 2003 to 2017, there were several subsidence regions and one uplift region in Los Angeles.

The cumulative subsidence was -266.8 mm at the maximum, and the average annual subsidence velocity was -19 mm/yr, which was mainly caused by groundwater overexploitation.

The maximum amount of accumulated lift is +104.8 mm, and the average annual lifting velocity can reach +7.5 mm/yr.

Our results have very strong practical application value and can provide a significant basis for local government services in disaster prevention and mitigation decision-making.

American Psychological Association (APA)

Hu, Bo& Chen, Xiongle& Zhang, Xingfu. 2019. Using Multisensor SAR Datasets to Monitor Land Subsidence in Los Angeles from 2003 to 2017. Journal of Sensors،Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1191850

Modern Language Association (MLA)

Hu, Bo…[et al.]. Using Multisensor SAR Datasets to Monitor Land Subsidence in Los Angeles from 2003 to 2017. Journal of Sensors No. 2019 (2019), pp.1-15.
https://search.emarefa.net/detail/BIM-1191850

American Medical Association (AMA)

Hu, Bo& Chen, Xiongle& Zhang, Xingfu. Using Multisensor SAR Datasets to Monitor Land Subsidence in Los Angeles from 2003 to 2017. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-15.
https://search.emarefa.net/detail/BIM-1191850

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1191850