The survey on surface subsidence around Xinglongzhuang coal mine based on remote sensing

2013 ◽  
pp. 141-146
Author(s):  
Haiqing Wang ◽  
Xiaohong Wang ◽  
Jinzhong Yang ◽  
Yingjie Zhou ◽  
Jie Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Coal Mine ◽  
Surface Subsidence

Delineation and mapping of coal mine fire using remote sensing data – a review

2018 ◽  
Vol 40 (17) ◽  
pp. 6499-6529 ◽  
Author(s):  
Shanti Swarup Biswal ◽  
Simit Raval ◽  
Amit Kumar Gorai
Keyword(s):  
Remote Sensing ◽  
Coal Mine ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Mine Fire ◽  
Coal Mine Fire

scholarly journals Surface Subsidence Prediction Method for Coal Mines with Ultrathick and Hard Stratum

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Hongkai Han ◽  
Jialin Xu ◽  
Xiaozhen Wang ◽  
Jianlin Xie ◽  
Yantuan Xing
Keyword(s):  
Coal Mining ◽  
Coal Mine ◽  
Prediction Method ◽  
Prediction Equation ◽  
Arbitrary Cross Section ◽  
Surface Subsidence ◽  
Strong Impact ◽  
Subsidence Prediction ◽  
Movement Characteristics ◽  
Mining Condition

Overburden conditions consisting of ultrathick and hard stratum (UTHS) are widespread in China and other countries, but existing surface subsidence prediction methods ignore the strong impact of UTHS on surface subsidence. They are thus not applicable for surface subsidence prediction for coal mining with the presence of UTHS. We conducted actual measurements of surface and UTHS subsidence in the Tingnan Coal Mine. The results showed that under the UTHS mining condition, the required gob dimension is much larger than the empirical value when the surface reaches sufficient mining and that the actual measured maximum value of surface subsidence is much smaller than the empirical value. The UTHS subsidence is approximately equal to the surface subsidence. The movement of UTHS has a strong impact on surface subsidence and has a controlling function for it. It was proposed that surface subsidence could be approximately predicted by calculating the UTHS subsidence. The UTHS movement characteristics were studied using Winkler’s theory of beams on an elastic foundation, the subsidence prediction equation of the main sections in the strike and dip directions was obtained under different mining dimensions, and the subsidence prediction equation of any arbitrary cross section parallel to the two main sections was established. Then, the surface subsidence prediction method for coal mining with the presence of UTHS was developed, and the influences of UTHS thickness, strength, and layer position on the surface subsidence were discussed. The Tingnan Coal Mine was taken as an example, and the subsidence curves of the strike and dip main sections were calculated using different mining dimensions. Subsequently, the surface subsidence after the mining of working faces 204, 205, 206, and 207, respectively, was predicted, and the prediction method was verified by comparing the results with the measured surface subsidence results of working faces 204, 205, and 206.

scholarly journals Remote Sensing Monitoring of Soil Moisture in the Daliuta Coal Mine Based on SPOT 5/6 and Worldview-2

2019 ◽  
Vol 11 (1) ◽  
pp. 866-876
Author(s):  
Ying Liu ◽  
Hui Yue
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Scale Effect ◽  
Coal Mine ◽  
Surface Soil ◽  
Underground Mining ◽  
Mining Area ◽  
Surface Soil Moisture ◽  
Temporal And Spatial ◽  
Spot 5

Abstract To understand the influence of underground mining disturbances on the shallow soil moisture in the Daliuta coal mine, remote sensing monitoring of the temporal and spatial evolution of surface soil moisture and the influence of mining on multi-source, multi-temporal and high spatial resolution remote sensing data were carried out. The scale effect of monitoring the soil moisture at different scales was analyzed using the Scaled Soil Moisture Monitor Index (S-SMMI). In this paper, SPOT 5/6 and Worldview-2 were used as the data source and mainly made up two aspects of the research: 1) based on the three SPOT data sets with the use of S-SMMI from different angles from the Daliuta mine from nearly three years of soil moisture temporal and spatial changes, the results show that the perturbation has a negative effect on the shallow soil moisture in the Daliuta coal mine, and average soil moisture of the mining area is smaller than the non-mining area, but the surface ecological construction has effectively improved the impact of the underground mining disturbance on the surface soil moisture. 2) the scale conversion of Worldview-2 data was carried out based on the resampling method. S-SMMI was used to analyze the scale effect of soil moisture monitoring at different scales. The results show that the difference between the soil moisture is only 0.0016 during the conversion process of 2 m-30 m.

REMOTE SENSING, VISUALIZATION AND MODELING OF THE DIAMOND COAL MINE IN HAZLETON, PA

2004 ◽  
Vol 2004 (1) ◽  
pp. 1728-1749
Author(s):  
Daniel Sirkis ◽  
◽  
Glendon Stevens ◽  
Dr. Timothy Bechtel
Keyword(s):  
Remote Sensing ◽  
Coal Mine

Laser remote sensing of methane in a working coal mine

1985 ◽  
Author(s):  
R. K. DEFREEZ ◽  
R. A. ELLIOTT ◽  
W. D. EGAN ◽  
R. T. BOOS
Keyword(s):  
Remote Sensing ◽  
Coal Mine ◽  
Laser Remote Sensing

scholarly journals The Impact of Coal Exploitation on Tidal Flat Changes, an Investigation Using Remote Sensing Data in Vietnam

2021 ◽  
Vol 1 (2) ◽  
Author(s):  
Thi Lan PHAM ◽  
Si Son TONG ◽  
Thi Thu Ha LE ◽  
Thi Le LE ◽  
Huu Duc HOANG
Keyword(s):  
Remote Sensing ◽  
Coal Mining ◽  
Coal Mine ◽  
Tidal Flat ◽  
Remote Sensing Data ◽  
Tidal Flats ◽  
Mining Activities ◽  
Landsat Images ◽  
Sensing Data ◽  
The Impact

Tidal flat plays a crucial role in socio-economic development and ecological environment.Tidal flats in Ha Long-Cam Pha in Vietnam are impacted by human activities, especially coal miningactivities. Using remote sensing data is able to detect, extract, and monitor the changes of tidal flats andexploited coal mine area with multi-temporal, in various scales, and for a large coverage. This studyaims to investigate the impact of coal mining activities on the changes of tidal flats using remote sensingin Cam Pha, Ha Long, one of the biggest coal basins in Vietnam. Digital Elevation Models (DEMs) oftidal flats constructed by Landsat satellite images acquired in years 1989, 2001, and 2014 are comparedto determine the volume changes. Besides, coal mining activities including coal production, waste rockdump area, and the expansion of open coal mine during the period 1989-2014 are investigated usingcorrespondent Landsat images and the reports from the coal mine companies in the study area. Sedimentsamples in tidal flats are analyzed to determine the origin of the sediments. As the results, organic matterin the tidal flats is dominant with the concentration of 459 g/kg to 607 g/kg, which is evidence for theimpact of coal exploitation on the coastal environment. In addition, the relationship between coal mineactivities and tidal flat variation is well observed in this study.

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