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Identification of geothermal potential based on land surface temperature derived from remotely sensed data
Jianyu Liu1, Jiangqin Chao1,2, Zhifang Zhao3,4,5,6
1Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650500, China.
Environmental Science and Pollution Research International
|September 14, 2023
Summary
Identifying geothermal potential areas using thermal infrared remote sensing is crucial. This study found three promising geothermal anomalies in Longyang, western Yunnan, with the mono-window algorithm proving most accurate for surface temperature inversion.
Area of Science:
- Geophysics
- Remote Sensing
- Geothermal Energy Exploration
Background:
- Thermal infrared remote sensing and surface temperature inversion algorithms are key for identifying geothermal potential.
- The eastern Longyang region in western Yunnan is known for geothermal resources, but its distribution is unclear.
Purpose of the Study:
- To identify high-temperature anomalous areas indicative of geothermal potential in eastern Longyang.
- To evaluate and select the optimal surface temperature inversion algorithm for the study area.
- To delineate geothermal prospective areas using a multi-view remote sensing approach.
Main Methods:
- Utilized Landsat-8 TIRS data and four surface temperature inversion algorithms: mono-window, single-channel, Du split window (SWD), and Jiménez-Muñoz split window (SWJ).
- Cross-validated inversion results with Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST) data.
- Employed a multi-view remote sensing method combining threshold, fracture structure buffer, and diurnal temporal data analysis to refine thermal anomaly areas.
Main Results:
- The mono-window algorithm demonstrated the highest accuracy (Pearson coefficient of 0.77), making it suitable for surface temperature inversion in Longyang.
- Three geothermal anomalies (A, B, and C) were identified, with anomalies A and C showing larger thermal signatures and significant development potential.
- All identified anomalies were verified by existing hot spring points.
Conclusions:
- The mono-window algorithm is recommended for accurate surface temperature inversion in the Longyang region.
- Areas A and C represent significant geothermal development potential, supported by verified hot spring occurrences.
- This study provides a robust methodological framework for geothermal resource exploration using remote sensing in similar regions.
Keywords:
Geothermal resource forecastLongyang East RegionMulti-view extraction of thermal anomaliesSurface temperature inversionMore Related Videos
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