# Identification of Industrial Heat Source Production Areas Based on SDGSAT-1 Thermal Infrared Imager
## 1 Introduction  
Industrial heat source production areas (IHSPAs) specifically refer to areas where waste heat is released from working industrial plants, such as from the smelting and rolling of nonferrous metals in oil refineries and exploration fields, cement plants, and chemical processing plants [1]. Industrial heat sources (IHSs) serve as the primary source of production for numerous economic sectors, providing essential material and technical foundations for a country's total energy consumption [2, 3]. Heat emissions from IHSs are the main source of anthropocentric heat emissions [4], regional air pollution, andanthropomorphic carbon emissions [5, 6]. In 2022, global carbon dioxide (CO\({}_{2}\)) emissions originating from energy combustion and industrial processes experienced a growth of 0.9% and reached a new all-time high of 36.8 gigatons (Gt) according to recent data [7]. Long-term air pollution not only harms human health but also impedes the green and healthy development of nature. What is more, the detection of IHSPAs can also be used to observe the production statuses of factories [8, 9]. Therefore, it has become fairly important to detect IHSPAs objectively and accurately to support environmental monitoring and industrial decision making. Many studies have examined the industrial waste heat potential from the perspectives of energy efficiency and policy [10, 11]. Some have concentrated on national- or regional-level heat emissions [12, 13] via inventory-based methods, energy balance residuals, the construction of energy models [14], multi-methods [15], and statistical regression methods [13, 16, 17]. Estimations of waste heat that can be recovered, used again, and utilized by various technologies are one of the key goals of these investigations. However, these methods are limited to exploring the waste heat generated by manufacturing facilities and do not extend to the detection and monitoring of IHSs on a large scale. Moreover, inventory-based methods have difficulty mapping or detecting IHSPAs precisely and objectively from regional to larger scales because of the high subjectivity, time consumption, and data limits [4, 17, 18]. Recently, high-resolution optical [19] and thermal remote sensing data have been widely utilized to detect and monitor changes in IHSs in large-scale areas [20, 21, 22]. [PERSON] et al. [19] identified key equipment by using high-resolution optical images obtained from Worldview and then monitored the illegal and irregular construction of steel firms in Shijiazhuang. However, it is difficult to detect whether firms are working or not, or even to estimate their heat emissions. As a result of its sensitivity to information regarding surface thermal radiation, thermal infrared remote sensing is commonly employed to monitor changes in surface temperatures [20, 22, 23, 24] using the VIIRS night-fire product (750 m) in conjunction with spatial and temporal features to detect global heat sources. To detect IHSs in small areas by using an adaptive K-means algorithm, VIIRS active fire point data (ACF, 375 m) with a greater spatial resolution were introduced [21]. Later, [PERSON] used VIIRS ACF data to analyze the spatial distribution of heavy IHSs in India based on K-means clustering and threshold identification models combined with nighttime lighting data [25]. The results showed that this detection technique is superior to the \"clustering-threshold\" technique in terms of accuracy. [PERSON] extracted heat source objects from 2013 data with an accuracy of 97.30% by using VIIRS ACF data combined with DBSCAN clustering and logistic regression clustering algorithms [26]. However, such methods can detect only the approximate locations of IHSs. It is difficult to detect IHSPAs and IHSs lower than 500 K and smaller than 1 \(\times\) 10\({}^{5}\) m\({}^{2}\)[27].