scholarly journals InSAR monitoring surface deformation induced by underground mining using Sentinel-1 images

2020 ◽  
Vol 382 ◽  
pp. 237-240
Author(s):  
Ling Zhang ◽  
Daqing Ge ◽  
Xiaofang Guo ◽  
Bin Liu ◽  
Man Li ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Surface Deformation ◽  
Underground Mining ◽  
Deformation Gradient ◽  
Mining Area ◽  
Interferometric Synthetic Aperture Radar ◽  
Mining Areas ◽  
Temporal Decorrelation ◽  
Land Deformation ◽  
Small Baseline

Abstract. Land subsidence can be caused by underground mining activities. Interferometric Synthetic Aperture Radar (InSAR) has became an economic, effective and accurate technique for land deformation survey and monitoring. In mining areas, there may be several factors to overcome for the succsessful application of InSAR, such as temporal decorrelation and detectable deformation gradient, that limit the ability of InSAR to monitoring rapid land subsidence. In this paper, images obtained by the Sentinel-1 satellite with 6 or 12 d revisiting time are used to improve the ability to detect a deformation gradient, and reduce the influence of temporal decorrelation. By combining Small Baseline Subsets (SBAS) and Interferometric Point Target Analysis (IPTA) methods, using the Nanhu mining area in Tangshan as an example, the spatial continuous results of land subsidence in this mining area are obtained with a 70 cm per year maximum rate, which clearly characterizes the deformation field and its deformation process. The results show that InSAR is a useful way to monitor land subsidence in a mining area and provides further data for environment mine restoration.

scholarly journals SBAS-InSAR Based Deformation Detection of Urban Land, Created from Mega-Scale Mountain Excavating and Valley Filling in the Loess Plateau: The Case Study of Yan’an City

2019 ◽  
Vol 11 (14) ◽  
pp. 1673 ◽  
Author(s):  
Qiong Wu ◽  
Chunting Jia ◽  
Shengbo Chen ◽  
Hongqing Li
Keyword(s):  
Loess Plateau ◽  
Land Subsidence ◽  
Surface Deformation ◽  
Land Uplift ◽  
Synthetic Aperture Radar Interferometry ◽  
Urban Buildings ◽  
Small Baseline Subset ◽  
Land Deformation ◽  
Small Baseline ◽  
Sbas Insar

Yan’an new district (YND) is one of the largest civil engineering projects for land creation in Loess Plateau, of which the amount of earthwork exceeds 600 million m3, to create 78.5 km2 of flat land. Such mega-scale engineering activities and complex geological characteristics have induced wide land deformation in the region. Small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) method and 55 Sentinel-1A (S-1A) images were utilized in the present work to investigate the urban surface deformation in the Yan’an urban area and Yan’an new airport (YNA) from 2015 to 2019. The results were validated by the ground leveling measurements in the YNA. It is found that significant uneven surface deformation existed in both YND and YNA areas with maximum accumulative subsidence of 300 and 217 mm, respectively. Moreover, the average subsidence rate of the YND and YNA areas ranged from −70 to 30 mm/year and −50 to 25 mm/year, respectively. The present work shows that the land deformation suffered two periods (from 2015 to 2017 and from 2017 to 2019) and expanded from urban center to surrounding resettlement area, which are highly relevant with urban earthwork process. It is found that more than 60% of land subsidence occurs at filled areas, while more than 65% of surface uplifting occurs at excavation areas. The present work shows that the subsidence originates from the earth filling and the load of urban buildings, while the release of stress is the major factor for the land uplift. Moreover, it is found that the collapsibility of loess and concentrated precipitation deteriorates the degree of local land subsidence. The deformation discovered by this paper shows that the city may suffer a long period of subsidence, and huge challenges may exist in the period of urban maintaining buildings and infrastructure facilities.

scholarly journals INSAR COLLABORATIVE MONITORING MODE AND MULTI-MODE COMPUTING SERVICES FOR GEOHAZARDS IDENTIFICATION IN OPEN-PIT MINING AREA

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 241-247
Author(s):  
J. Zhang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Underground Mining ◽  
Mining Area ◽  
Deformation Monitoring ◽  
High Density ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mining Areas ◽  
Wide Range

Abstract. InSAR has developed a variety of methods, such as D-InSAR, PS-InSAR, MBAS, CT, SqueeSAR, POT, etc., which have been widely used in land subsidence monitoring. For open pit mining areas, there are usually mining activity, complex terrain features, low coherence, and local large deformation gradients, which makes it difficult for time series InSAR technology to obtain high-density surface deformation information in open pit mining areas. Traditional methods usually only monitor the linear deformation of the surface caused by the mining of a few working zone above the underground mining area, and the temporal and spatial resolution is lower. How to obtain high-precision, high-density, and time-sensitive deformation information is the main difficulty of InSAR monitoring in open pit mining areas. Make full use of the geosensor network monitoring system, optimize monitoring mode of collaborated satellite-to-ground based InSAR, further realize whole calculation and geographic information services, to achieve early identification and discovery of abnormal in large-area macro-monitoring, and accurate monitoring of local areas in real-time early warning, which is the development direction of ground deformation monitoring of mining areas. The study area is Pingshuo open pit mining area. we fully study the application mode and services of InSAR monitoring for geohazards in open-pit mining area, through the establishment of satellite InSAR technology system for large-scale macro-monitoring and forecasting, and GBSAR and GSN for local precision monitoring. The effective mode of InSAR monitoring of geohazard in open-pit mines is summarized. A combination of D-InSAR, POT (Pixel offset tracking), Time Series-InSAR and GB-SAR is used in a wide range, and high-resolution optical images are used to identify localized changes in subsidence areas and open-pit mining areas.

scholarly journals Method Combining Probability Integration Model and a Small Baseline Subset for Time Series Monitoring of Mining Subsidence

2018 ◽  
Vol 10 (9) ◽  
pp. 1444 ◽  
Author(s):  
Hongdong Fan ◽  
Lu Lu ◽  
Yahui Yao
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Deformation Gradient ◽  
Mining Area ◽  
Mining Subsidence ◽  
Interferometric Synthetic Aperture Radar ◽  
Integration Model ◽  
Small Baseline Subset ◽  
Maximum Subsidence ◽  
Small Baseline

Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) has high accuracy for monitoring slow surface subsidence. However, in the case of a large-scale mining subsidence areas, the monitoring capabilities of TS-InSAR are poor, owing to temporal and spatial decorrelation. To monitor mining subsidence effectively, a method known as Probability Integration Model Small Baseline Set (PIM-SBAS) was applied. In this method, mining subsidence with a large deformation gradient was simulated by a PIM. After simulated deformation was transformed into a wrapped phase, the residual wrapped phase was obtained by subtracting the simulated wrapped phase from the actual wrapped phase. SBAS was used to calculate the residual subsidence. Finally, the mining subsidence was determined by adding the simulated deformation to the residual subsidence. The time series subsidence of the Nantun mining area was derived from 10 TerraSAR-X (TSX) images for the period 25 December 2011 to 2 April 2012. The Zouji highway above the 9308 workface was the target for study. The calculated maximum mining subsidence was 860 mm. The maximum subsidence for the Zouji highway was about 145 mm. Compared with the SBAS method, PIM-SBAS alleviates the difficulty of phase unwrapping, and may be used to monitor large-scale mining subsidence.

scholarly journals Land deformation associated with exploitation of groundwater in Changzhou City measured by COSMO-SkyMed and Sentinel-1A SAR data

2018 ◽  
Vol 10 (1) ◽  
pp. 678-687 ◽  
Author(s):  
Deliang Chen ◽  
Yanyan Lu ◽  
Dongzhen Jia
Keyword(s):  
Land Subsidence ◽  
Yangtze River ◽  
Yangtze River Delta ◽  
Groundwater Exploration ◽  
River Delta ◽  
Urban Agglomeration ◽  
Land Deformation ◽  
Small Baseline ◽  
Groundwater Rebound ◽  
Sbas Insar

Abstract The Urban Agglomeration in Yangtze River Delta is one of the most important economic and industrial regions in China. The City of Changzhou is one of the most important industrial citys in Yangtze River Delta Urban Agglomeration. Activities here include groundwater exploration. Groundwater overexploitation has contributed to the major land deformation in this city. The severity and magnitude of land deformation over time were investigated in Changzhou City. A Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology, provides a useful tool in measuring urban land deformation. In this study, a time series of COSMO-SkyMed and Sentinel-1A SAR images covering Changzhou City were acquired. SBAS-InSAR imaging technique was used to survey the extent and severity of land deformation associated with the exploitation of groundwater in Changzhou City. Leveling data was used to validate the SBAR-InSAR productions, the error of SBAR-InSAR annual subsidence results was within 2 mm. The results showed that three main land subsidence zones were detected at Xinbei, Tianning and Wujin District. Four subsidence points were selected to analyze the temporal and spatial evolution characteristics of land subsidence. The subsidence rate of P1 to P4 was −2.48 mm/year, −12.78 mm/year, −18.09 mm/year, and −12.69 mm/year respectively. Land subsidence over Changzhou showed a trend of slowing down from 2011 to 2017, especially in Wujin District. SBAR-InSAR derived land deformation that correlates with the water level change in six groundwater stations. Indicated that with groundwater rebound, the land rebound obviously, and the maximum rebound vale reached 9.13 mm.

scholarly journals MONITORING OF LAND SUBSIDENCE IN RAVENNA MUNICIPALITY USING INTEGRATED SAR - GPS TECHNIQUES: DESCRIPTION AND FIRST RESULTS

2016 ◽  
Vol XLI-B7 ◽  
pp. 23-28 ◽  
Author(s):  
G. Artese ◽  
S. Fiaschi ◽  
D. Di Martire ◽  
S. Tessitore ◽  
M. Fabris ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Interferometric Synthetic Aperture Radar ◽  
Persistent Scatterers ◽  
Gps Measurement ◽  
Measurement Results ◽  
Prone Area ◽  
First Results ◽  
Emilia Romagna Region ◽  
Small Baseline Subset ◽  
Small Baseline

The Emilia Romagna Region (N-E Italy) and in particular the Adriatic Sea coastline of Ravenna, is affected by a noticeable subsidence that started in the 1950s, when the exploitation of on and off-shore methane reservoirs began, along with the pumping of groundwater for industrial uses. In such area the current subsidence rate, even if lower than in the past, reaches the -2 cm/y. Over the years, local Authorities have monitored this phenomenon with different techniques: spirit levelling, GPS surveys and, more recently, Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques, confirming the critical situation of land subsidence risk. In this work, we present the comparison between the results obtained with DInSAR and GPS techniques applied to the study of the land subsidence in the Ravenna territory. With regard to the DInSAR, the Small Baseline Subset (SBAS) and the Coherent Pixel Technique (CPT) techniques have been used. Different SAR datasets have been exploited: ERS-1/2, ENVISAT, TerraSAR-X and Sentinel-1. Some GPS campaigns have been also carried out in a subsidence prone area. 3D vertices have been selected very close to existing persistent scatterers in order to link the GPS measurement results to the SAR ones. GPS data were processed into the International reference system and the comparisons between the coordinates, for the first 6 months of the monitoring, provided results with the same trend of the DInSAR data, even if inside the precision of the method.

scholarly journals Land Subsidence Related to Coal Mining in China Revealed by L-Band InSAR Analysis

2020 ◽  
Vol 17 (4) ◽  
pp. 1170
Author(s):  
Liping Zheng ◽  
Lin Zhu ◽  
Wei Wang ◽  
Lin Guo ◽  
Beibei Chen
Keyword(s):  
Synthetic Aperture Radar ◽  
Coal Mining ◽  
Land Subsidence ◽  
Ordos Basin ◽  
Coal Mines ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Geological Disasters ◽  
Land Deformation ◽  
The Ordos Basin

Geological disasters, including ground deformation, fractures and collapse, are serious problems in coal mining regions, which have threatened the sustainable development for local industry. The Ordos Basin is most known for its abundant coal resources. Over-mining the underground coal resources had induced land deformation. Detecting the evolution of the land deformation features and identifying the potential risk are important for decision-makers to prevent geological disasters. We analyzed land subsidence induced by coal mining in a 200 km 2 area in the Ordos Basin for the time period 2006–2015. ALOS-1 PALSAR images from December 2006 to January 2011 and ALOS-2 PALSAR-2 images from December 2014 to July 2015, optical remotely sensed images and coal mining information were collected. The small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) method and differential interferometric synthetic aperture radar (D-InSAR) method, GIS and statistical analysis were adopted. Results show that the maximum subsidence rate and cumulative subsidence along the line of sight (LOS) were −65 mm/year and −246 mm, respectively, from December 2006 to January 2011. The maximum cumulative subsidence was −226 mm from December 2014 to July 2015. The new boundary of the mining goafs from 2014 to 2015 and the most dangerous risk region were mapped. Moreover, the effect of large-scale mining coal, with the production volume exceeds 1.2 million tons per year, with the operation time more than 20 years on land subsidence was found greater than small and medium-scale coal mines and reached −59 mm/year. The recently established small-sized and medium-sized coal mines show high land subsidence. This study will contribute to better understand the land subsidence process in mining region and provide scientific support for government to prevent land subsidence.

Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification

2019 ◽  
Vol 11 (14) ◽  
pp. 1719 ◽  
Author(s):  
Jiaxin Mi ◽  
Yongjun Yang ◽  
Shaoliang Zhang ◽  
Shi An ◽  
Huping Hou ◽  
...  
Keyword(s):  
Land Use ◽  
Random Forest ◽  
Land Cover ◽  
Large Scale ◽  
Underground Mining ◽  
Mining Area ◽  
Random Forest Classifier ◽  
Land Use Land Cover ◽  
Lulc Change ◽  
Mining Areas

Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

scholarly journals Slope ranking and geohazards correlation analysis for combined open-underground mining area

2018 ◽  
Author(s):  
Zhang Jin
Keyword(s):  
Correlation Analysis ◽  
Water Conservation ◽  
Laser Scanning ◽  
Underground Mining ◽  
Mining Area ◽  
Open Pit ◽  
Ground Subsidence ◽  
Data Sets ◽  
Mining Areas ◽  
Factor Data

Geohazards in mining areas are mainly ground subsidence, slope landslides and ground cracks, surface cover degradation and environmental ecological pattern destruction. The classification and rank of terrain slope and the feature area extraction of the slope are the important content for the correlation analysis with the geohazards. The slope classification and rank index system for soil and water conservation, land use and man-made ground disasters was analyzed. According to the characteristics of open pit and underground associated mining area, we comprehensively analyzed the spatial correlation between different ground disaster and terrain features and landform types, and propose a new slope ranking index, dividing slope zones and forming slope classification map. Especially slope area of 35-45 degrees and more than 45 degrees was extracted, and the relationship between regional geohazards and slope zone was analyzed. The application of terrestrial laser scanning technology to establish open-pit high precision digital elevation model, extraction of slope, slope type, gully density characteristic factor, topography factor data sets are established, and correlation analysis, to enhance disaster information content.

scholarly journals MINING LAND SUBSIDENCE MONITORING USING SENTINEL-1 SAR DATA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 655-658 ◽  
Author(s):  
W. Yuan ◽  
Q. Wang ◽  
J. Fan ◽  
H. Li
Keyword(s):  
Law Enforcement ◽  
Land Subsidence ◽  
Coal Mine ◽  
Underground Mining ◽  
Mining Area ◽  
Mine Area ◽  
Optical Images ◽  
Sar Data ◽  
Comparison Of The Results ◽  
Subsidence Monitoring

In this paper, DInSAR technique was used to monitor land subsidence in mining area. The study area was selected in the coal mine area located in Yuanbaoshan District, Chifeng City, and Sentinel-1 data were used to carry out DInSAR techniqu. We analyzed the interferometric results by Sentinel-1 data from December 2015 to May 2016. Through the comparison of the results of DInSAR technique and the location of the mine on the optical images, it is shown that DInSAR technique can be used to effectively monitor the land subsidence caused by underground mining, and it is an effective tool for law enforcement of over-mining.

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