## 5 Discussion
### Limitations and Future Improvements  
While this study successfully applies thermal infrared (TIR) remote sensing for geothermal anomaly detection, recognizing its limitations and identifying areas for future improvement are essential to enhance accuracy and reliability.  
Figure 13: Spatial Relationship Between Day–Night Combined Geothermal Anomalies and Inferred Magmatic Chamber Locations in the Study Area; **(a)** Overall distribution in the study area; **(b)** Yangbajing region; **(c)** Regaguo and Yangjingxue regions **(d)** Yangyi region.  
1. Limitations of Remote Sensing (RS) Data and the Need for Multi-Source Integration: RS data alone cannot fully capture the complexity of geothermal systems. Although TIR remote sensing effectively detects surface temperature anomalies, it cannot directly reveal subsurface features, such as fluid pathways, heat sources, or geological structures. Therefore, integrating remote sensing results with in situ validation methods--such as geophysical surveys, geochemical sampling, and borehole data--is crucial for improving interpretation accuracy and confirming geothermal targets [77, 78, 79].  
2. Potential Benefits of Multiband Data: While TIR remote sensing is widely used in geothermal anomaly detection, its dependence on thermal infrared bands may lead to omission of key spectral indicators. For instance, incorporating shortwave infrared (SWIR) bands can enhance the identification of hydrothermal alteration minerals, such as alunite, kaolinite, and muscovite, which are closely associated with geothermal activity. Combining TIR and SWIR data can improve mineralogical interpretation and more effectively delineate geothermal anomaly zones [27, 80, 81, 82, 83, 84, 85, 86].  
3. Impact of Surface Thermal Property Differences: Variations in the thermal properties of different land-cover types can significantly affect heat retention, conductivity, and surface temperature patterns. These differences may lead to spatial inconsistencies in LST data. Future research should incorporate high-resolution land-cover data or apply advanced classification techniques to address these differences and improve anomaly detection accuracy [20].  
4. Influence of Topographic Effects on LST Variations: Despite the use of winter data to minimize solar radiation interference, slope and aspect effects on LST in mountainous terrain remain a significant challenge. South-facing slopes typically receive more solar radiation and exhibit higher temperatures, while north-facing slopes remain cooler. Although elevation correction in this study partially mitigated these effects, developing more refined slope correction models is essential for improving temperature normalization and enhancing detection accuracy in rugged terrain [87, 88].  
5. Impact of Human Activities and Mitigation Strategies: Although anthropogenic heat islands have limited impact in this study area due to low population density, urban environments may exhibit elevated temperatures that obscure geothermal signals. Future studies could incorporate auxiliary datasets, such as nighttime light data, to identify and mask anthropogenic heat sources, thereby improving the precision of geothermal anomaly detection in densely populated regions.  
Addressing these limitations through improved data integration, advanced spectral analysis, refined terrain correction, and mitigation of anthropogenic effects will substantially enhance the accuracy and reliability of TIR remote sensing in geothermal exploration.