Evaluating land subsidence by field survey and D-InSAR technique in Damaneh City, Iran

Ghazifard, Akbar; Akbari, Elham; Shirani, Koroush; Safaei, Homayon

doi:10.1007/s40333-017-0104-5

Cited by 18 publications

(9 citation statements)

References 24 publications

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“…Land subsidence is defined as a gradual settling or sudden sinking of the ground surface [1,2,3], which results from natural processes or human activities [4,5,6,7]. Over the past decades, numerous land subsidence events have been reported in many cities around the world where the rapid urban construction and the extensive groundwater exploitation are taking place [8,9,10,11,12,13]. Land subsidence can lead to serious environmental problems and considerable economic losses, such as damage to infrastructures and increased risk of urban pluvial flooding [14,15,16,17,18].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data

Zhang

Liu

Jin

et al. 2019

Sensors

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Wuhan city is the biggest city in central China and has suffered subsidence problems in recent years because of its rapid urban construction. However, longtime and wide range monitoring of land subsidence is lacking. The causes of subsidence also require further study, such as natural conditions and human activities. We use small baseline subset (SBAS) interferometric synthetic aperture radar (InSAR) method and high-resolution RADARSAT-2 images acquired between 2015 and 2018 to derive subsidence. The SBAS-InSAR results are validated by 56 leveling benchmarks where two readings of elevation were recorded. Two natural factors (carbonate rock and soft soils) and three human factors (groundwater exploitation, subway excavation and urban construction) are investigated for their relationships with land subsidence. Results show that four major areas of subsidence are detected and the subsidence rate varies from −51.56 to 27.80 millimeters per year (mm/yr) with an average of −0.03 mm/yr. More than 83.81% of persistent scattered (PS) points obtain a standard deviation of less than −6 mm/yr, and the difference between SBAS-InSAR method and leveling data is less than 5 mm/yr. Thus, we conclude that SBAS-InSAR method with Radarsat-2 data is reliable for longtime monitoring of land subsidence covering a large area in Wuhan city. In addition, land subsidence is caused by a combination of natural conditions and human activities. Natural conditions provide a basis for subsidence and make subsidence possible. Human activities are driving factors and make subsidence happen. Moreover, subsidence information could be used in disaster prevention, urban planning, and hydrological modeling.

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Section: Introductionmentioning

confidence: 99%

Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data

Zhang

Liu

Jin

et al. 2019

Sensors

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“…As a typical active microwave imaging sensor, synthetic aperture radar (SAR) has the abilities of all-day and all-weather observation [1]. It has been broadly applied in many fields, such as natural resources surveys, topographic mapping, ground object extraction and disaster monitoring [2]. Decision tree (DR), support vector machine (SVM), Markov random field (MRF), deep learning and other artificial intelligence technologies have been introduced into the processing and analysis of remote sensing information [3][4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…In the above studies, the following issues should be noted: (1) Simulated data are often used in the experiments [2,[4][5][6][7][8][9][10]; thus, the detection result will be affected once the ideal data are replaced with the real SAR image. (2) DEM data are the essential auxiliary data [3,5,[7][8][9][10], and detection cannot be performed while the DEM of the study area is absent.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Layover Detection in Mountainous Areas with SAR Images

Wang

et al. 2021

Remote Sensing

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It is well known that there are geometric distortions in synthetic aperture radar (SAR) images when the terrain undulates. Layover is the most common one, which brings challenges to the application of SAR remote sensing. This study proposes a novel detection method that is mainly aimed at the layover caused by mountains and can be performed with only medium-resolution SAR images and no other auxiliary data. The detection includes the following four stages: initial processing, difference image calculation and rough and fine layover detection. Initial processing mainly obtains the potential layover areas, which are mixed with the built-up areas after classification. Additionally, according to the analysis of the backscatter coefficient (BC) of various ground objects with different polarization images, the layover areas are detected step-by-step from the mixed areas, in which the region-based FCM segmentation algorithm and spatial relationship criteria are used. Taking the Danjiangkou Reservoir area as the study area, the relevant experiments with Sentinel-1A SAR images were conducted. The quantitative analysis of detection results adopted the figure of merit (FoM), and the highest accuracy was up to 87.6% of one selected validation region. Experiments in the South Taihang area also showed the satisfactory effect of layover detection, and the values of FoM were all above 85%. These results show that the proposed method can do well in the layover detection caused by mountains. Its simplicity and effectiveness are helpful in removing the influence of layover on SAR image applications to a certain extent and improving the development of SAR remote sensing technology.

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“…A concerted effort has been made by several researchers to explore related aspects on ground subsidence (Abidin et al, 2013;Ghazifard et al, 2017). The most examined aspects are; monitoring of the subsidence and its prediction.…”

Section: Introductionmentioning

confidence: 99%

Application of microgravity and electrical resistivity imaging techniques to identify ground subsidence prone zone

Mohammed¹

2021

Acta Geodynamica Et Geomaterialia

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Owing to the disastrous consequences of ground subsidence in the urban area, great attention had always been accorded to areas with suspected signs of subsidence occurrence in order to mitigate its effect. Microgravity and electrical resistivity imaging (ERI) survey techniques were conducted at a parking lot of which possible occurrence of subsidence is anticipated due to the increased exposure of surface cracks and very slight depression. This study aimed to map and delineate the subsurface condition of the area with the view of revealing probable subsidence prone zones within the study area. To this end, the microgravity survey data was acquired at a station interval of 2 m. Pole-dipole configuration with 2 m electrode separation was adopted for the electrical resistivity imaging survey. The two methods showed good correlation with each other and proved their effectiveness in imaging the subsurface. A large proportion of the subsurface area was found to be residual soil (mainly silt and or clayey sand) with saturated zones identified by low gravity (< -40.94 mGal) and resistivity (<150 Ω.m) values, which have the tendency to undergo expansion and contraction processes due to rise and fall in moisture content. The subsurface condition was found to be relatively stable, devoid of any subsidence triggering features such as voids or cavities. However, it is inferred to be unsuitable for engineering structures due to the expansive and contractive properties of the subsurface geomaterials (residual soil). Therefore, it is concluded that the area is not prone to subsidence and the surface cracks presents are mere effects of the expansion and contraction process, which could be avoided by the excavation of the expansive soil or good engineering design before the establishment of any structure.

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Evaluating land subsidence by field survey and D-InSAR technique in Damaneh City, Iran

Cited by 18 publications

References 24 publications

Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data

Monitoring Land Subsidence in Wuhan City (China) using the SBAS-InSAR Method with Radarsat-2 Imagery Data

A Novel Method for Layover Detection in Mountainous Areas with SAR Images

Application of microgravity and electrical resistivity imaging techniques to identify ground subsidence prone zone

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