Accuracy Verification and Correction of D-InSAR and SBAS-InSAR in Monitoring Mining Surface Subsidence

Chen, Yang; Yu, Shengwen; Qing, Tao; Liu, Guolin; Wang, Luyao; Wang, Fengyun

doi:10.3390/rs13214365

Cited by 40 publications

(5 citation statements)

References 31 publications

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“…AHP is a flexible quantitative method, which has become one of the commonly used methods in risk assessment [60][61][62][63][64]. Based on the relevant literature and engineering requirements to determine the influencing factors affecting the surface subsidence monitoring program [14,[65][66][67], a total of three primary indicators and 16 secondary indicators are included, as shown in Figure 4 (natural factors and target constraints are determined in advance):…”

Section: Preference Model 231 Infactors Determination and Analysismentioning

confidence: 99%

Construction of “Space-Sky-Ground” Integrated Collaborative Monitoring Framework for Surface Deformation in Mining Area

Yan

Dai

et al. 2022

Remote Sensing

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Ground deformation measurements in mining areas play a key role in revealing the surface subsidence law, retrieving the subsidence parameters, warning of geological disasters and restoring the surface ecology. With the development of science and technology, there have emerged a great number of monitoring techniques and buildings of diverse protection levels. The diversity of monitoring techniques and the multiplicity of monitoring objects have brought challenges for surface deformation monitoring in the coal industry. Based on the existing deformation monitoring techniques, this paper established a framework of "space-sky-ground" collaborative monitoring system in mining area. We also constructed an AHP-TOPSIS (Analytic Hierarchy Process method- Technique for Order Preference by Similarity to an Ideal Solution) preference model of "space-sky-ground" collaborative monitoring of surface deformation in mining area, and carried out engineering application. Our study shows that the framework of the "space-sky-ground" collaborative monitoring system for surface subsidence in mining areas established in this paper, combined with the AHP-TOPSIS monitoring preference model, which can fully combine the advantages of each monitoring technique, overcome the limitations of a single monitoring technique, comprehensively obtain the surface subsidence data and work out the surface deformation subsidence pattern. This information provides a data and technical support for surface environment management.

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Section: Preference Model 231 Infactors Determination and Analysismentioning

confidence: 99%

Construction of “Space-Sky-Ground” Integrated Collaborative Monitoring Framework for Surface Deformation in Mining Area

Yan

Dai

et al. 2022

Remote Sensing

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“…Therefore, due to the differences in scattering characteristics in different areas of variable radar reflection regions, whether it is sparse persistent scatterers with high coherence or the interferometric fringe, this will make the single traditional interferometry methods, such as PS-InSAR or SBAS-InSAR, have limitations. At present, some studies [25][26][27][28] have only simply superimposed the two techniques and failed to consider the advantages and disadvantages of each of them. Experience with using PS-InSAR and SBAS-InSAR has shown that PSCs with higher-order coherence in PS-InsSAR are generally distributed in those point targets of urban built-up areas, and SDFP pixels in SABS-InSAR are generally distributed in those distributed targets of countryside vegetation areas, which causes PS-InSAR to have better accuracy in urban built-up areas, and SABS-InSAR has better accuracy in countryside vegetation areas.…”

Section: Introductionmentioning

confidence: 99%

Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR Techniques

Zhang

Guo

et al. 2022

Remote Sensing

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In the InSAR solution, the uneven distribution of permanent scatterer candidates (PSCs) or slowly decoherent filtering phase (SDFP) pixel density in a region of variable radar reflection feature can cause local low accuracy in single interferometry. PSCs with higher-order coherence in Permanent Scatter InSAR (PS-InSAR) are generally distributed in those point targets of urban built-up areas, and SDFP pixels in Small Baseline Subset InSAR (SBAS-InSAR) are generally distributed in those distributed targets of countryside vegetation areas. According to the respective reliability of PS-InSAR and SBAS-InSAR for different radar reflection features, a new land subsidence monitoring method is proposed, which combines PS-SBAS InSAR by data fusion of different interferometry in different radar reflection regions. Density-based spatial clustering of applications with noise (DBSCAN) clustering analysis is carried out on the density of PSCs with higher-order coherence in PS-InSAR processing to zone the region of variable radar reflection features for acquiring the boundary of data fusion. The vector monitoring data of PS-InSAR is retained in the dense region of PSCs with higher-order coherence, and the vector monitoring data of SBAS-InSAR is used in the sparse region of PSCs with higher-order coherence. The vertical displacements from PS-InSAR and SBAS-InSAR are integrated to obtain the optimal land subsidence. The verification case of 38 SAR images acquired by the Sentinel-1A in Suzhou city indicates that the proposed method can automatically choose a matched interferometry technique according to the variability of radar reflection features in the region and improve the accuracy of using a single interferometry method. The integrated method of the combined field is more representative of overall subsidence characteristics than the PS-InSAR-only or SBAS-InSAR-only results, and it is better suited for the assessment of the impact of land subsidence over the study area. The research results of this paper can provide a useful comprehensive reference for city planning and help decrease land subsidence in Suzhou.

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“…It is thus difficult to obtain valid measurements, which seriously affects the accuracy of the results. The application of the continuum D-InSAR technique has been widely proposed in the literature to monitor coal mining subsidence with rapid deformation (Przyłucka et al, 2015;Pawluszek-Filipiak and Borkowski, 2020;Chen et al, 2021). Interestingly, this method can acquire high precision surface deformation data in mine areas where no high gradient deformation has occurred.…”

Section: Introductionmentioning

confidence: 99%

Decision-making fusion of InSAR technology and offset tracking to study the deformation of large gradients in mining areas-Xuemiaotan mine as an example

Yang

Zhu

et al. 2022

Front. Earth Sci.

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The multi-level disturbance of underground and surface caused by coal mining activities intensifies the deterioration of the ecological environment in the mining area. Among them, the uneven settlement caused by coal mining is the most intuitive manifestation of surface environmental damage. The uneven settlement in the mining area has the characteristics of large settlement magnitude and severe deformation. Therefore, based on 15 Sentinel-1A image data, this paper uses three methods: SBAS InSAR, continuous D-InSAR and offset tracking technology to monitor the surface deformation of the mining area. The results show that the continuous D-InSAR technology SBAS-InSAR technology is applied to the small deformation in the edge area of the subsidence basin. The mining area with low gradient subsidence of SBAS-InSAR can obtain better performance than continuous D-InSAR technology. The offset tracking technique is used to monitor the large gradient deformation in the center of the subsidence basin. Therefore, this paper proposes to expand the quantitative analysis through the spatial coherence threshold and the accuracy and successful image elements of the interference fringe displacement. Combine the advantages of the three methods and overcome the shortcomings of each method, fuse the deformation information of the three methods, and obtain the deformation law of the whole surface subsidence. The results show that the mean absolute error (MAE1-1) of continuity D-InSAR is 0.92 m, the mean absolute error (MAE2-1) of SBAS-InSAR is 0.94 m, and the mean absolute error (MAE3-1) of Offset-tracking is 0.25 m. The results of this fusion method are in good agreement with the measured data, and the mean absolute error (MAE4-1) of vertical displacement is 7 cm. Therefore, the fusion method has advantages over individual methods and provides a new idea in monitoring the large gradient deformation of coal mining subsidence in mining areas.

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Accuracy Verification and Correction of D-InSAR and SBAS-InSAR in Monitoring Mining Surface Subsidence

Cited by 40 publications

References 31 publications

Construction of “Space-Sky-Ground” Integrated Collaborative Monitoring Framework for Surface Deformation in Mining Area

Construction of “Space-Sky-Ground” Integrated Collaborative Monitoring Framework for Surface Deformation in Mining Area

Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR Techniques

Decision-making fusion of InSAR technology and offset tracking to study the deformation of large gradients in mining areas-Xuemiaotan mine as an example

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