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Remote Sensing Technology and Application  2021, Vol. 36 Issue (6): 1368-1378    DOI: 10.11873/j.issn.1004-0323.2021.6.1368
    
Research on Quantitative Prediction and Evaluation of Geothermal Anomaly Area in Qamdo-Nyingchi Section of Sichuan-Tibet Railway
Zhe Chen1,2,3(),Qing Dong2(),Jianping Chen1,3,Wenbo Zhao2,5,Liangwen Jiang4,Guangze Zhang4,Tao Feng4,Dong Wang4,Xiaojia Bi4,Min Bian2,5,Quanping Zhang1,3,Deli Meng2,5
1.School of Earth Science and Resources,China University of Geosciences(Beijing),Beijing 100083,China
2.Laboratory of Digital Earth Science,Aerospace Information Research Institute,CAS,Beijing 100094,China
3.Key Laboratory of Land and Resources Information Research & Development in Beijing,Beijing 100083,China
4.China Railway Eryuan Engineering Group Co. Ltd,Chengdu 610031,China
5.University of Chinese Academy of Sciences,Beijing 100049,China
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Abstract  

The identification of geothermal anomaly areas along the Sichuan-Tibet Railway is helpful to the construction and later management and maintenance of the project. Taking The Qamdo-Nyingchi section of Sichuan-Tibet Railway as the research area, based on the landsat-8 thermal infrared image data, the surface temperature was inverted and the planetary geostationary experiment was carried out to obtain the corrected geotherm value. Focusing on the genesis and distribution of geothermal anomalies, six influencing factors, namely, formation assemblage entropy, fault buffer distance, fault line density, surface temperature, water buffer distance, and peak ground motion acceleration, were selected as the evaluation indexes of geothermal anomaly areas and the independence of factors was tested. An information quantity model was built for quantitative prediction, and the recognition results were finally divided into 5 sub-regions. The results show that the high anomaly area and the middle anomaly area account for 9.14% and 28.57% of the total area of the study area respectively, and the spatial distribution of geothermal high-temperature points is basically consistent with the evaluation results of geothermal anomaly area. The research results can provide reference for the design and construction of Sichuan-Tibet railway.

Key words:  Sichuan-Tibet Railway      Thermal infrared remote sensing      Surface temperature      Information model      Geothermal anomaly region     
Received:  06 October 2020      Published:  26 January 2022
ZTFLH:  P642.2  
Corresponding Authors:  Qing Dong     E-mail:  chenz115@foxmail.com;dongqing@aircas.ac.cn
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Articles by authors
Zhe Chen
Qing Dong
Jianping Chen
Wenbo Zhao
Liangwen Jiang
Guangze Zhang
Tao Feng
Dong Wang
Xiaojia Bi
Min Bian
Quanping Zhang
Deli Meng

Cite this article: 

Zhe Chen,Qing Dong,Jianping Chen,Wenbo Zhao,Liangwen Jiang,Guangze Zhang,Tao Feng,Dong Wang,Xiaojia Bi,Min Bian,Quanping Zhang,Deli Meng. Research on Quantitative Prediction and Evaluation of Geothermal Anomaly Area in Qamdo-Nyingchi Section of Sichuan-Tibet Railway. Remote Sensing Technology and Application, 2021, 36(6): 1368-1378.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2021.6.1368     OR     http://www.rsta.ac.cn/EN/Y2021/V36/I6/1368

Fig.1  Overview of research area and synchronous experimental area
Fig.2  The relation of measured temperature and inversion temperature
Fig.3  Surface temperature before and after calibration
Fig.4  Images impact factor
指标因子地层组合熵断层缓冲距断层线密度地表温度水系缓冲距地震烈度
地层组合熵1.000
断层缓冲距-0.0811.000
断层线密度0.143-0.2701.000
地表温度-0.004-0.0620.1431.000
水系缓冲距-0.0240.091-0.068-0.1531.000
地震烈度-0.132-0.0180.1290.072-0.0091.000
Table 1  The correlation between index factors
影响因子分级地热点 个数/个面积 /km2信息量
地层组合熵0~1049124 419-0.361
10~20913 1230.188
20~401925 9820.252
40~501013 4250.270
50~601313 6920.513
60~802222 3170.551
80~10048 694-0.211

断层缓冲距

/km

0~25328 1451.198
2~42824 1670.712
4~61020 690-0.162
6~81017 3160.016
8~10514 973-0.532
10~12412 839-0.601
>1216103 522-1.302
断层线密度 /(km/km2)0.000~0.0121599 114-1.323
0.012~0.033723 838-0.661
0.033~0.0533545 1910.309
0.053~0.0741818 4000.543
0.074~0.0982521 1030.734
0.098~0.1281710 3911.057
0.128~0.18093 6151.477
地表温度 /℃-10~-6076 0090.000
-6~01151 784-0.984
0~61838 579-0.197
6~113226 3440.789
11~163517 7021.247
16~22248 7681.572
22~4362 4661.454
水系缓冲距 /km0~25529 4341.190
2~41427 588-0.113
4~61226 126-0.213
6~81024 261-0.321
8~10721 523-0.558
10~12918 524-0.157
>121974 197-0.797
地震烈度 /级786147 7190.029
83869 796-0.043
924 137-0.162
单元栅格尺寸为30 m×30 m,计算时面积可用对应的栅格数目替代
Table 2  Results of information values
Fig.5  Favorability image for the information model
地热异常分级地热点数地热点占比网格单元数网格单元占比成功指数
高异常区6350.00%22 396 6399.14%0.000 28%
中异常区3628.57%50 748 93120.70%0.000 07%
低异常区1411.11%51 387 18820.96%0.000 03%
异常缓冲区97.14%47 482 52919.37%0.000 02%
无异常区43.17%73 133 05929.83%0.000 01%
Table 3  Success indices for favorability obtained from favorability image
Fig.6  Curves of prediction ratio function
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