Search

Due to a heavy reliance on groundwater, Bangladesh is experiencing a severe decline in groundwater storage, with some areas even facing land subsidence. This study aims to investigate the relationship between groundwater storage changes and land subsidence in Bangladesh, utilizing a combination of GRACE and InSAR technologies. To clarify this relationship from a macro perspective, the study employs GRACE data merged with GLDAS to analyze changes in groundwater storage and SBAS-InSAR technology to assess land subsidence. The Dynamic Time Warping (DTW) method calculates the similarity between groundwater storage and land subsidence time series, incorporating precipitation and land cover types into the data analysis. The findings reveal the following: (1) Groundwater storage in Bangladesh is declining at an average rate of −5.55 mm/year, with the most significant declines occurring in Rangpur, Mymensingh, and Rajshahi. Notably, subsidence areas closely match regions with deeper groundwater levels; (2) The similarity coefficient between the time series of groundwater storage and land subsidence changes exceeds 0.85. Additionally, land subsidence in different regions shows an average lagged response of 2 to 6 months to changes in groundwater storage. This study confirms a connection between groundwater dynamics and land subsidence in Bangladesh, providing essential knowledge and theoretical support for further research. [ABSTRACT FROM AUTHOR]

This brief article gathers several improvements to the LiCSBAS, an open-source python-based InSAR time series tool developed by the COMET UK group, focusing on improving quality of unwrapped interferograms that are the input to the time series inversion, therefore their quality is crucial. We add functionality of full re-unwrapping of the original wrapped interferograms using a procedure controlled by several key parameters. We then check the residuals of phase loop closure residuals and either nullify pixels in interferograms that probably contain unwrapping error, or attempt to correct the errors within connected components or pixel-wise using some basic assumptions, such as the minimal residue of the unwrapped data from a preliminary model estimate (whole time series velocity) is correct. All these approaches find their importance in different case studies and will be part of the next version of LiCSBAS. [ABSTRACT FROM AUTHOR]

Due to a heavy reliance on groundwater, Bangladesh is experiencing a severe decline in groundwater storage, with some areas even facing land subsidence. This study aims to investigate the relationship between groundwater storage changes and land subsidence in Bangladesh, utilizing a combination of GRACE and InSAR technologies. To clarify this relationship from a macro perspective, the study employs GRACE data merged with GLDAS to analyze changes in groundwater storage and SBAS-InSAR technology to assess land subsidence. The Dynamic Time Warping (DTW) method calculates the similarity between groundwater storage and land subsidence time series, incorporating precipitation and land cover types into the data analysis. The findings reveal the following: (1) Groundwater storage in Bangladesh is declining at an average rate of −5.55 mm/year, with the most significant declines occurring in Rangpur, Mymensingh, and Rajshahi. Notably, subsidence areas closely match regions with deeper groundwater levels; (2) The similarity coefficient between the time series of groundwater storage and land subsidence changes exceeds 0.85. Additionally, land subsidence in different regions shows an average lagged response of 2 to 6 months to changes in groundwater storage. This study confirms a connection between groundwater dynamics and land subsidence in Bangladesh, providing essential knowledge and theoretical support for further research.

Surface deformation analysis plays a crucial role in understanding geodetic phenomena and their implications for hazard assessment, infrastructure management, and environmental studies. In recent years, the incorporation of synthetic aperture radar (InSAR) and advanced processing techniques have been used to monitor surface deformation. One such technique, LiCSBAS, has shown great promise in analyzing InSAR time series data to accurately detect and quantify surface displacements. It has been successfully employed in various geodetic monitoring scenarios such as landslide monitoring, infrastructure stability assessment, and volcanic deformation analysis. In this study, studies were reviewed in which performance evaluation and comparison of LiCSBAS with other technologies were discussed as well as future developments and challenges in this field. The results of a review of previous studies show the effectiveness of LiCSBAS in detecting and analyzing surface deformation, allowing for a better understanding of geodetic processes. This overview will provide a set of ideas that will assist stakeholders involved in surface deformation analysis and geodetic monitoring and contribute to decision-making to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Objectives: Multi-temporal interferometric synthetic aperture radar (InSAR) technology is widely used in deformation monitoring over wide areas due to its characteristics of large-scale, high spatial-temporal resolution and the capability to monitor deformation signal with millimeter precision even submillimeter. For the time-consuming problem in acquiring image and data preprocessing over research area, this paper uses looking inside the continents from space with synthetic aperture radar (LiCSAR) products and takes a new time series analysis LiCSBAS method, which greatly improve the computational efficiency. Methods: The quality check and the closure error of the phase loop are used to detect the unwrapping error in the two-dimensional phase unwrapping, and the interferogram with low coherence and the large error pixels are excluded. To minimize atmospheric artifacts, utilizing the generic atmospheric correction online service for In‑ SAR (GACOS) products and based on this, a method for joint estimation of deformation and atmospheric phase is proposed. Taking the Chengdu Plain and western mountainous area as the study area, totally 90 [ABSTRACT FROM AUTHOR]

Landslides are a common type of disaster in Indonesia, especially in steepslope areas. The landslide process can be well understood by measuring the surface deformation. Currently, there are no practical solutions for measuring surface deformation at landslide locations other than field surveys in the Pacitan Regency. We apply LiCSBAS, to identify surface deformation in several landslide locations in a specific non-urban area with mixed topographical features. LiCSBAS is a module that utilizes data from the project of looking inside the continent from space (LiCS), using the new small baseline area subset (NSBAS) method. This study utilizes the leaf area index (LAI) to validate the ability of LiCSBAS to detect surface deformation values at landslide locations. The study succeeded in identifying surface deformations at 100 landslide locations, with deformation values ranging from 15.1 to 10.9 millimeters per year. Most of the landslide locations are closely related to volcanic rocks and volcanic sediments on slopes of 30-35°. The NSBAS method in the LiCSBAS module can reduce gaps error in the sentinel-1 image network. However, the utilization of the C-band at a pixel size of 100 meters made surface deformation only well detectable in a large open landslide area. [ABSTRACT FROM AUTHOR]

Objectives: The Sichuan Tibet Railway crosses the Jinsha River specifically the section from Xiongsong Town to Shadong Town, Gongjue County, Tibet Autonomous Region, in which exist strong topography variations and many potential geohazards, and hence it urgent to detect the potential geohazards in this region to ensure the railway safety. Methods: In this paper, 61 Sentinel -1 ascending, 53 Sentinel -1 descending and 7 advanced land observing satellite 2 (ALOS 2) ascending images are used to derive the annual mean deformation rates in the satellite radar line of sight (LOS) with two advanced InSAR (interferometric synthetic aperture radar) approaches, namely generic atmospheric correction online service for InSAR (GACOS) assisted InSAR Stacking and LiCSBAS. The three LOS annual mean deformation rate maps are then used to determine 2D surface movements (one along the slope and the other perpendicular to the slope) in the study region. Results: The comparison between GACOS assisted InSAR Stacking and LiCSBAS results show that they agree with each other with correlation coefficients over 0.92 for the LOS deformation rates and over 0.85 for the 2D deformation rates, suggesting the reliability of GACOS assisted InSAR Stacking. The maximum annual deformation rate of 163 mm/a can be observed in the slope direction and seven landslides (A, B, C, D, E, F, G) can be clearly identified, which in turn lays the foundation for future real-time monitoring. Based on the detailed analysis of the seven regions by using InSAR and optical interpretation results, it is found that the seven landslides had relatively obvious deformation. Landslides A, B, C and D are active landslides, which might cause the result of river blocking due to overall instability. At present, landslides E, F and G are still in the stage of slow deformation. Conclusions: This study also find that GACOS assisted InSAR Stacking can effectively remove long band and topographic related atmospheric delay error with the help of GACOS, which has the advantages of being simple, effective, fast, and easy to popularize and apply. GACOS assisted InSAR Stacking technology can be used to quickly identify potential landslide hazards. [ABSTRACT FROM AUTHOR]

Landslide is a natural phenomenon that frequently occurs on the Java Island of Indonesia, causing significant damage and casualties. Due to advances in remote sensing technology, radar imaging can detect and evaluate ground surface deformation. This study examines the ground surface deformation and displacement in each landslide location in terms of spatial and temporal and identifies the different types and characteristics of landslides in the Sukabumi area of West Java, Indonesia. The Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) methodology was used in this study, and the DinSAR method was applied. We combined the LiCSAR data product with the Python coding-based LiCSBAS processing package to derive a surface displacement value at each landslide location. The results show that the DinSAR approach can detect surface deformation by integrating the LiCSAR product with the Python coding-based LiCSBAS processing software. According to quantitative data, the research area experienced surface deformation with a surface displacement velocity of -36,297 mm/year to 58,837 mm/year. The ground surface displacement at each landslide location ranged from -9.79 mm/year to +33.69 mm/year, with most of the landslides occurring on moderate to steep slopes (160-350). These results are suitable to use for support regional development planning in reducing losses and casualties. [ABSTRACT FROM AUTHOR]

On January 27, 2017, the Indonesian Government started building a new international airport in Yogyakarta Province, named Yogyakarta International Airport (YIA) to replace Adisucipto International Airport. YIA is located near the beach, which means that an awareness of natural disasters, such as coastal flooding, is essential. One of the causes of sea water flooding is land subsidence phenomenon. This land subsidence phenomenon can be monitored by using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) data. To monitor the crustal deformation, the data used in this research are from years 2016-2019. The data were processed through LiCSBAS software which is published by the COMET in the UK. In the processing scheme, interferograms with many unwrapping errors are detected and removed via loop closure. Reliable time series and velocities are extracted using several noise indices, with the help of masking. The results show the subsidence phenomenon in the YIA area (up to 25 mm). [ABSTRACT FROM AUTHOR]