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Subsidence of a Coal Ash Landfill in a Power Plant Observed by Applying PSInSAR to Sentinel-1 SAR Data

Authors :
Youngnam Shin
Hoonyol Lee
Source :
Remote Sensing, Vol 15, Iss 17, p 4127 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

We analyzed ground subsidence at the coal ash disposal sites of Stanton Energy Center, a power plant located in Orlando, Florida, USA, by applying 157 Sentinel-1 SAR images obtained between May 2017 and December 2022 in ascending orbit to the PSInSAR technique. A LiDAR DEM with 1 m posting was used for the DInSAR and StaMPS processing for PSInSAR. The results showed significant ground subsidence on the area where solar panels were installed on top of the coal ash landfill. The coal ash landfill was divided into three sites (A, B, and C) according to the landfill sequence. The spatially averaged PSInSAR showed subsidence rates of 7.3 mm/year, 6.2 mm/year, and 8.8 mm/year in sites A, B, and C, respectively. In particular, relatively newly deposited sites A and B showed a decreasing trend in subsidence rate with higher quadratic components in regression function, indicating a stabilization of the subsidence. On the other hand, the oldest site C exhibited the highest (and a relatively constant) subsidence rate, suggesting that the settlement occurred earlier and is now at a constant rate. It is also suspected that new dumping activity near C might have caused a higher subsidence rate than in sites A and B. No subsidence occurred at other solar panel installations on the ground outside the landfill, suggesting that the subsidence was caused by the gravitational compaction of the landfill materials rather than by the instability of the solar facilities. Comparison of PSInSAR results with lower resolution DEMs, such as SRTM and Copernicus DEM, showed range errors of the PS positions proportional to the height deviation from LiDAR DEM, highlighting the importance of accurate DEMs for the time-series analysis of SAR data.

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
17
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.1fd4fab8899443499d2530ff04be4ed
Document Type :
article
Full Text :
https://doi.org/10.3390/rs15174127