Land Subsidence and Groundwater Storage Assessment Using ICOPS, GRACE, and Susceptibility Mapping in Pekalongan, Indonesia

Floods in Pekalongan, Indonesia, often occur due to river water overflowing during heavy monsoon rain. Simultaneously, the northern coastal area of Pekalongan, located adjacent to the Java Sea, has been affected by coastal floods due to sea level rise. The flood conditions in this area were exacerba...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2023, Vol.61, p.1-25
Main Authors: Hakim, Wahyu Luqmanul, Fadhillah, Muhammad Fulki, Lee, Kwang-Jae, Lee, Seung-Jae, Chae, Sung-Ho, Lee, Chang-Wook
Format: Article
Language:English
Subjects:
Algorithms
Alluvial deposits
Alluvium
Analysis
Aquifers
Artificial neural networks
Coastal zone
Compression
Convolutional neural network (CNN)
Convolutional neural networks
Deep learning
Deformation
Environmental monitoring
Flood mapping
Flooding
Floods
Geographic information systems
Geographical information systems
Global positioning systems
GPS
GRACE (experiment)
Gravity
Groundwater
Groundwater data
Groundwater storage
Hazard mitigation
Hot spots
improved combined scatterers interferometry with optimized point scatterers (ICOPS)
Information systems
Interferometric synthetic aperture radar
Interferometry
interferometry synthetic aperture radar (InSAR)
Land subsidence
Machine learning
Mapping
Monitoring
Neural networks
Pore pressure
Pore water pressure
Radar
Radar satellites
Rainfall
Remote sensing
River water
Rivers
SAR (radar)
Satellite navigation systems
Satellite tracking
Satellites
Sea level changes
Sea level rise
Sea measurements
Soil compaction
Statistical analysis
Subsidence
susceptibility
Synthetic aperture radar
Time series
Urban areas
Water monitoring
Weather stations
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Summary:Floods in Pekalongan, Indonesia, often occur due to river water overflowing during heavy monsoon rain. Simultaneously, the northern coastal area of Pekalongan, located adjacent to the Java Sea, has been affected by coastal floods due to sea level rise. The flood conditions in this area were exacerbated by land subsidence, leading to coastal inundation. Monitoring land subsidence in Pekalongan has become essential in predicting other possible land subsidence occurrence areas and mitigating the possible hazards caused by land subsidence. The analysis of land subsidence has been much easier since the introduction of radar satellites. In this study, 124 synthetic aperture radar (SAR) datasets from the Sentinel-1 radar satellite between 2017 and 2022 in descending tracks were used. The data were processed through a time-series interferometry SAR (InSAR) method based on the improved combined scatterers interferometry with optimized point scatterers (ICOPS) algorithm to provide accurate measurements over large areas by improving the selection of measurement points (MPs) from persistent scatterer (PS) and distributed scatterer (DS) points using a deep learning algorithm based on a convolutional neural network (CNN), and the resulting optimized MPs were then spatially clustered using optimized hot spot analysis (OHSA) to estimate significant points statistically and define them as hot spot points. The results of time-series deformation in Pekalongan were compared with the GPS station measurements. From the comparison, a good correlation in terms of deformation patterns between time-series InSAR and GPS measurements was observed. Our study revealed that land subsidence in Pekalongan has occurred mostly in settlement areas under the young alluvium soil, which cannot support many buildings' maximum compression. Another cause of land subsidence in Pekalongan is excessive groundwater extraction in settlement areas. Thus, compaction in the aquifer areas may occur as a result of the reduced effective stress of the pore pressure. Further analysis of this study would involve monitoring groundwater activity using data from the Gravity Recovery and Climate Experiment (GRACE) satellite and comparing them with weather station data. The analysis of the two datasets aims to understand the relationships between groundwater storage data and the monthly precipitation in Pekalongan. Finally, the potential outcomes of land subsidence in Pekalongan will be assessed using the geographic
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2023.3324043