An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

Huang, Jianhui; Deng, Kazhong; Fan, Hongdong; Lei, Shaogang; Yan, Song Y.; Wang, Lei

doi:10.1155/2017/3059159

Cited by 20 publications

(11 citation statements)

References 49 publications

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“…The searching patterns are detected on the basis of values of accumulated votes higher than the predefined threshold value. The Hough transform [ 20 ] together with methods based on the convolution of the image with a bank of circular wavelets [ 12 ], template recognition [ 21 ], or deep convolutional neural network [ 22 ] were used for the deformation patterns detection in the SAR interferograms. None of them proved to be capable of the reliable detection of irregular circular fringes on the noisy SAR interferograms.…”

Section: Introductionmentioning

confidence: 99%

Automatic Subsidence Troughs Detection in SAR Interferograms Using Circlet Transform

Bała

Dwornik

Franczyk

2021

Sensors

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This article presents the results of automatic detection of subsidence troughs in synthetic aperture radar (SAR) interferograms. The detection of subsidence troughs is based on the circlet transform, which is able to detect features with circular shapes. Compared to other methods of detecting circles, the circular transform takes into account the finite data frequency. Moreover, the search shape is not limited to a circle but identified on the basis of a certain width. This is especially important in the case of detection of subsidence troughs whose shapes may not be similar to circles or ellipses but to their fragments. The transformation works directly on the image gradient; it does not require further binary segmentation or edge detection as in the case of other methods, e.g., the Hough transform. The entire processing process can be automated to save time and increase reliability compared to traditional methods. The proposed automatic detection method was tested on a differential interferogram that was generated based on Sentinel-1A SAR images of the Upper Silesian Coal Basin area. The test carried out showed that the proposed method is 20% more effective in detecting troughs that than the method using Hough transform.

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Section: Introductionmentioning

confidence: 99%

Automatic Subsidence Troughs Detection in SAR Interferograms Using Circlet Transform

Bała

Dwornik

Franczyk

2021

Sensors

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“…InSAR technique has been applied to monitor the land subsidence in coal mining area [17][18][19][20][21][22][23][24][25][26][27][28][29][30]. Ji et al [18] demonstrated InSAR's ability to cost-effectively monitor illegal mining activities.…”

Section: Introductionmentioning

confidence: 99%

Monitoring, Analyzing, and Modeling for Single Subsidence Basin in Coal Mining Areas Based on SAR Interferometry with L-Band Data

Wang

Zhang

et al. 2021

Scientific Programming

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Excessive exploitation of underground mine resources has caused serious land subsidence in China. This paper focused on monitoring and modeling the single subsidence basin in coal mining area based on SAR interferometry (InSAR). The optimum InSAR processing strategy to monitor the mining subsidence was built to obtain the land subsidence with large deformation. And a method of three-dimensional mathematical modeling of single subsidence basin based on InSAR measurements was presented. Using Jining Coalfield (China) as the study area, we acquired 7 L-band PALSAR images from January 2008 to February 2010 to monitor the land subsidence in Jining Coalfield. The deformation maps in Jining Coalfield in different periods were obtained. Taking the Geting Coal Mine within the Jining coalfield as an example, we finely analyzed and interpreted the deformation maps. Compared with the simultaneous filed measurements, the precision of deformation measurement using D-InSAR in mining area was analyzed. The root mean square error was 1.37 cm. The method of fine interpretation and analysis for a single subsidence basin was established. The experiments have proved that InSAR technique with L-band InSAR data is suitable for monitoring mining subsidence with large deformation. And the 3D mathematical modeling method could be used for the single subsidence basin in coal mining area.

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“…Literature research shows that there are mainly two types of approaches to solve the problems of full-scale gradient mining subsidence D-InSAR monitoring. The first method is single pass OT(Offset Tracking) / (InSAR and OT) + prior model monitoring method [18]- [20]. On the basis of high resolution SAR image, it is firstly to get largegradient LOS deformation of mining subsidence basin by OT technology.…”

Section: Introductionmentioning

confidence: 99%

Retrieving 3D Large Gradient Deformation Induced to Mining Subsidence Based on Fusion of Boltzmann Prediction Model and Single-Track InSAR Earth Observation Technology

Jiang

Wang

2021

IEEE Access

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Surface deformation of mining area caused by mining subsidence can be divided into three stages:the initial stage,the active stage and the decline stage.At the active stage,D-InSAR technology could be easily affected by the incoherence of large-gradient deformation,thus leading to the failure of conventional D-InSAR technology in monitoring mining subsidence.In order to solve the problem,this paper developed a 3D surface deformation prediction method of mining subsidence by integrating dynamic Boltzmann prediction model with D-InSAR.It was firstly to monitor the surface movement and deformation by D-InSAR technology during the decline stage and obtain the surface LOS deformation field data.Then,on the basis of Boltzmann model,the geometric equation between LOS deformation by D-InSAR monitored and 3D deformation was established. Next,the geometric equation was solved based on the GA theory,and the parameters of Boltzmann prior model were obtained.On the basis,the 3D deformation of mining area were obtained,proving that D-InSAR technology was effective to get 3D deformation of mining subsidence.Through simulation experiments,the effectiveness of the proposed method is verified.The surface deformation of 1613 working face in Guqiaonan coal mine was monitored by D-InSAR during the decline stage,and the LOS deformation values were obtained.The 3D deformation was obtained from the initial stage to the decline stage by using the method of DB-InSAR.The monitoring results showed that the fitting errors in the LOS deformation were mostly within 3 mm,the RMSES was ± 2.37 mm,shown that the fitting accuracy was high.The RMSE of subsidence were ±120 mm.The results showed that the method of DB-InSAR has engineering application values.

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An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

Cited by 20 publications

References 49 publications

Automatic Subsidence Troughs Detection in SAR Interferograms Using Circlet Transform

Automatic Subsidence Troughs Detection in SAR Interferograms Using Circlet Transform

Monitoring, Analyzing, and Modeling for Single Subsidence Basin in Coal Mining Areas Based on SAR Interferometry with L-Band Data

Retrieving 3D Large Gradient Deformation Induced to Mining Subsidence Based on Fusion of Boltzmann Prediction Model and Single-Track InSAR Earth Observation Technology

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