# Identification of Industrial Heat Source Production Areas Based on SDGSAT-1 Thermal Infrared Imager
## 5 Conclusions  
Large-scale heat and pollution emissions from IHSs can have serious impacts on environmental quality and human health and cause climate change and natural disasters. However, the existing methods are unable to accurately identify IHSPAs, and the granularity of the IHS identification is low. Therefore, SDGSAT-1 TIS data, which have the highest resolution (30 m) in the civilian field and a three-band advantage, were first introduced to detect IHSPAs and improve the granularity and accuracy of IHS detection. Then, an IHSPA identification model using SDGSAT-1 (TIS) and the combination of multi-feature extraction and SVM was proposed in this research. Some conclusions were obtained from different comparisons in Wuhai, China:  
1. IHSPA identification based on SVM using thermal and optical features from SDGSAT-1 TIS and Landsat-8 data can detect IHSPAs and obtain the best IHSPAs results compared with different features and identification models;
2. The importance of thermal features in model training was demonstrated by different importance analysis methods. T\({}_{1}\) from the SDGSAT-1 TIS had the largest importance weight;
3. Our proposed method can detect more IHSs with greater spatial coverage and smaller areas than the methods of [PERSON] [21] and [PERSON] [3]. The number of IHSs from our results was 5.22 times greater than the number from [PERSON]'s inventory and 7.88 times greater than the number from [PERSON]'s inventory. At the same time, the minimum identification area of our results was 0.03 km\({}^{2}\), rather than the 0.16 km\({}^{2}\) and 0.26 km\({}^{2}\) of [PERSON]'s and [PERSON]'s inventories, respectively.  
The results suggest that our method, due to improvements in the thermal infrared data resolution and sensitivity to low-temperature objects, may identify a greater number of factories with smaller scales and lower levels of thermal radiation. And industrial plants and mines can be monitored and evaluated more precisely by utilizing our IHSPA identification model employing SDGSAT-1 TIS data. This method could be useful to industry regulations and policymakers.  
Conceptualization, D.W., Y.X., C.M., Y.Z. and D.Y.; methodology, Y.X., C.M., Y.Z. and D.Y.; software, Y.X. and C.M.; validation, D.W. and Y.X.; formal analysis, Y.X. and C.M.; investigation, Y.X., C.M., Y.Z., D.Y., X.H., H.C., B.F. and G.W.; resources, C.M.; data curation, Y.X., C.M., Y.Z., D.Y., X.H., H.C., B.F. and G.W.; writing-original draft preparation, Y.X., C.M. and Y.Z.; writing--review and editing, D.W, Y.X., C.M., and Y.Z.; visualization, Y.X. and C.M.; supervision, C.M., Y.Z. and D.Y.; project administration, D.W, C.M., Y.Z. and D.Y.; funding acquisition, D.W. and C.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was supported by the National Key R&D Program of China (No. 2022 YFF0606402) and the Youth Innovation Promotion Association of the Chinese Academy of Science under Grant 2021126.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The authors acknowledge the free use of Landsat-8 OLI products ([[https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/)]([https://earthexplorer.usgs.gov/](https://earthexplorer.usgs.gov/)), accessed on 26 August 2022). The SDGSAT-1 TIS data were kindly provided by the International Research Center of Big Data for Sustainable Development Goals (CBAS).  
**Acknowledgments:** The authors thank the editors and the three anonymous reviewers for their valuable comments, which helped to improve our manuscript.  
**Conflicts of Interest:** The authors declare no conflicts of interest.