Detection of geothermal potential based on land surface temperature derived from remotely sensed and in-situ data
文献类型：期刊论文
| 作者 | Zhao, Fei9; Peng, Zhiyan; Qian, Jiangkang1; Chu, Chen8; Zhao, Zhifang6,7,9; Chao, Jiangqin4,5; Xu, Shiguang3 |
| 刊名 | GEO-SPATIAL INFORMATION SCIENCE
 |
| 出版日期 | 2023-02-26 |
| 卷号 | N/A |
| 关键词 | Geothermal Detection Index (GDI) geothermal potential Principal Component Analysis (PCA) Land Surface Temperature (LST) |
| DOI | 10.1080/10095020.2023.2178335 |
| 文献子类 | Article ; Early Access |
| 英文摘要 | Geothermal energy is a renewable and environmentally sustainable resource of increasing importance. However, areas with geothermal potential are not easily detected by traditional field investigations, requiring the development of new, robust, and reliable models for detection. In this study, remote sensing data and ground-based variables were used to detect and analyze geothermal resource potential areas. General Land Surface Temperature (GLST) was integrated using 5 years of remote sensing data. Landsat 8 daytime GLST (Landsat-GLST), Moderate Resolution Imaging Spectroradiometer (MODIS) daytime GLST (MODIS-DLST), and MODIS nighttime GLST (MODIS-NLST) data were integrated with Landsat Nighttime Land Surface Temperature (Night-LST), which not only filled the gap of Landsat Night-LST but also improved the spatial resolution of MODIS nighttime temperatures. Specifically, three independent variables (Night-LST, Distance From Known Geothermal Resource Points [DFGP], and Distance From Geological Faults [DFF]) were used to develop a weighted model to form a Geothermal Detection Index (GDI) based on Principal Component Analysis (PCA). Along with field verification, the GDI was successfully used to identify three geothermal activity areas in Tengchong City, Yunnan Province. Overall, this work provides a novel method for detecting geothermal potential to support the successful exploitation of geothermal resources. |
| WOS关键词 | SPLIT-WINDOW ALGORITHM ; TIME-SERIES ; CHINA ; TENGCHONG ; RESOURCES ; RETRIEVAL ; PRODUCT ; AREA ; EXPLORATION ; ANOMALIES |
| WOS研究方向 | Remote Sensing |
| WOS记录号 | WOS:000943768000001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/200735]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Res Ctr Domest High resolut Satellite Remote Sensi, Kunming, Peoples R China 2.Yunnan Geol & Mineral Engn Explorat Grp Co, Kunming, Peoples R China 3.Zhaotong Univ, Sch Geog Sci & Tourism, Kunming, Peoples R China 4.Yunnan Univ, Inst Int Rivers & Ecosecur, Kunming, Peoples R China 5.Yunnan Prov Key Lab Sanjiang Metallogeny & Resourc, Kunming, Peoples R China 6.Minist Nat Resources, Key Lab Sanjiang Metallogeny & Resources Explorat, Kunming, Peoples R China 7.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 8.Univ Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China 9.Yunnan Univ, Sch Earth Sci, Kunming, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Fei,Peng, Zhiyan,Qian, Jiangkang,et al. Detection of geothermal potential based on land surface temperature derived from remotely sensed and in-situ data[J]. GEO-SPATIAL INFORMATION SCIENCE,2023,N/A. |
| APA | Zhao, Fei.,Peng, Zhiyan.,Qian, Jiangkang.,Chu, Chen.,Zhao, Zhifang.,...&Xu, Shiguang.(2023).Detection of geothermal potential based on land surface temperature derived from remotely sensed and in-situ data.GEO-SPATIAL INFORMATION SCIENCE,N/A. |
| MLA | Zhao, Fei,et al."Detection of geothermal potential based on land surface temperature derived from remotely sensed and in-situ data".GEO-SPATIAL INFORMATION SCIENCE N/A(2023). |
入库方式： OAI收割
来源：地理科学与资源研究所
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