[1]袁晶,陈艳,唐春花,等.遥感地热GIS预测方法研究——以江西宁都地区为例[J].华东地质,2023,44(04):424-438.[doi:10.16788/j.hddz.32-1865/P.2023.04.006]
　YUAN Jing,CHEN Yan,TANG Chunhua,et al.Remote sensing geothermal GIS prediction method—a case study in Ningdu City, Jiangxi Province[J].East China Geology,2023,44(04):424-438.[doi:10.16788/j.hddz.32-1865/P.2023.04.006]
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遥感地热GIS预测方法研究——以江西宁都地区为例()
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《华东地质》[ISSN:2096-1871/CN:32-1865/P]

卷:
44
期数:
2023年04期
页码:
424-438
栏目:
其他
出版日期:
2023-12-27

文章信息/Info

Title:
Remote sensing geothermal GIS prediction method—a case study in Ningdu City, Jiangxi Province
作者:
袁晶1; 2;  陈艳1;  唐春花1;  孙超1;  宛胜1;  钱正江1;  唐枭1;  汪明有1
1. 江西省地质调查勘查院, 江西南昌 330030;
2. 中国地质大学(北京)地球科学与资源学院, 北京 100083
Author(s):
YUAN Jing1; 2;  CHEN Yan1;  TANG Chunhua1;  SUN Chao1;  WAN Sheng1;  QIAN Zhengjiang1;  TANG Xiao1;  WANG Mingyou1
1. Jiangxi Geological Survey and Exploration Institute, Nanchang 330030, Jiangxi, China;
2. School of Earth Science and Resources, China University of Geosciences (Beijing), Beijing 100083, China
关键词:
遥感; 地热; 热红外; 预测因子; GIS技术; 宁都
Keywords:
remote sensing; geothermal; thermal infrared; predictors; GIS technology; Ningdu City
分类号:
P627P314
DOI:
10.16788/j.hddz.32-1865/P.2023.04.006
摘要:
遥感技术在地热资源调查与预测中被广泛应用。为解决传统遥感地热预测方法预测结果精度低、假异常多的问题,文章提出了一种遥感地热GIS预测方法。以江西宁都为研究区,开展了成热地质条件研究,分析了地质、遥感、物探等对地热的指示作用,进一步提出了地层、岩浆岩、控热断裂、控水断裂、断裂交汇、ETM+热红外反演温度、ASTER热红外反演温度、羟基异常、土壤湿度、高程、水系、航磁、重力等13个预测因子。运用证据权法、找矿信息量法和特征分析法开展了地热预测,经综合分析圈定地热有利区79处,其中A类12处、B类22处、C类45处。已知地热与A类、B类地热有利区吻合,部分A类地热有利区经野外查证发现地热异常,表明预测结果可信度较高。遥感地热GIS预测方法具有遥感数据多源、预测因子多、智能化等特征,是一种实用有效的预测方法,可作为地热资源调查中的一种常规技术方法使用。
Abstract:
Remote sensing technology is widely used in geothermal resource investigation and prediction. To solve the problems of the low accuracy and many false anomalies in the traditional remote sensing geothermal prediction, this paper presents a method of remote sensing geothermal GIS prediction. Taking Ningdu, Jiangxi Province as the research area, the study on thermal geological conditions was carried out, and the indication functions of geology, remote sensing and geophysical exploration on geothermal energy were analyzed. Furthermore, 13 predictive factors including strata, magmatic rocks, thermal control faults, water control faults, fault intersection, ETM+thermal infrared inversion temperature, ASTER thermal infrared inversion temperature, hydroxyl anomaly, soil moisture, elevation, water system, aero-magnetism and gravity were put forward. Geothermal prediction was carried out with the methods of evidence-weight, prospecting information and characteristic analysis, and 79 geothermal favorable areas consisting of 12 places of Class A, 22 Class B and 45 Class C were delineated through comprehensive analysis. The known geothermal distribution coincides with Class A and Class B favorable areas, and the Class A favorable areas were partially found with geothermal anomalies by the field investigation, indicating high reliability of the prediction. Remote sensing geothermal GIS prediction is a practical and effective method because of its multi-source remote sensing data, incremental prediction factors and intelligence, which can be used as a conventional technique in geothermal resource survey.

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备注/Memo

备注/Memo:
收稿日期:2022-11-20;改回日期:2023-03-28。
基金项目:江西省地质局"遥感方法在地热资源调查与预测中的应用"项目资助。
作者简介:袁晶,1986年生,男,高级工程师,硕士研究生,主要从事基础地质、矿产勘查及遥感地质工作。Email:southseafrog@126.com。
通讯作者:唐春花,1965年生,女,教授级高级工程师,本科,主要从事地质科研及遥感地质工作。Email:553827851@qq.com。
更新日期/Last Update: 1900-01-01