## 1 Introduction  
Chemical accidents (including chemical leakages, fires, and explosions) are prone to occur in industrial complexes where chemical substances are being handled. In South Korea, 711 chemical accidents occurred from January 2014 to September 2022, including 567 chemical leakages (approximately 80% of the total number of accidents) and 103 explosions (approximately 14%) [1]. For chemical accidents, risk reduction, and effective response to accidents, a monitoring system should be installed for each industrial complex to enable early detection and identification of an accident. However, industrial complexes are extensive and complex structures with large-scale chemical facilities where various chemical substances are handled. Thus, a monitoring system must comprise detection equipment in high locations to detect chemical accidents from a distance. In the event of chemical leakages, it is necessary to obtain real-time information on the identified toxic compounds and their concentrations and to identify the gas source and affected areas through images showing the location and size of the toxic gas cloud [2]. Among the different techniques, passive remote sensing technology with Fourier transform infrared (FTIR) spectroscopy is suitable for large-scale monitoring to detect and identify the gas clouds in the atmosphere [3; 4; 5]. These techniques are applied in various fields and studies where the composition of volcanic gases are measured remotely (e.g., SO\({}_{2}\) detection at 6 km in New Zealand in 1996; SO\({}_{2}\), and SiF\({}_{4}\) detection at 17 km in Mexico in 1997 [6]), the emissions from industrial facilities are analyzed [4; 7; 8], and the atmospheric environment is in analyzed [5; 9; 10; 11]. In the event of a fire, the areas where the chemical accident has occurred must be swiftly identified while observing the daytime or nighttime conditions of the industrial complex via real-time transmission of images. Long-range cameras and real-time video streaming with electro-optical (EO) and infrared (IR) systems enable the detection, recognition, and identification (DRI) of threats/targets from a distance; the warning signals are sufficiently fast for response actions [12]. Various researchers have used EO/IR sensors for different purposes, including the determination of the direction of a forest fire from smoke and heat signals [13], marine search and rescue [14], remote sensing of an air vehicle [15], and aerial monitoring of offshore oil spills [16]. Remote sensing change detection is a process used to identify changes by remote sensing images in various fields (including disaster assessment, urban studies, and environmental monitoring). A fuzzy topology-based majority voting model [17] and a novel higher-order clique conditional random field model [18] can be applied to unsupervised change detection. Recent studies related to environmental monitoring have used different detection technologies. The EU-SENSE is a system for real-time detection, monitoring, and analysis of chemical, biological, radiological, and nuclear threats and hazards. It was designed and developed as a heterogeneous sensor node that combines ion mobility spectrometry, flame photometry, and a metal oxide detector prototype [19]. In another case, a drone with sensors (photo ionization detectors and ion mobility spectrometry) and a sampling system is triggered by an alarm from a laser-based network when anomalies are detected. It is used for environmental monitoring and detects emission sources from industrial releases and forest fires [20]. In previous studies, individual pieces of equipment (including gas detectors and surveillance cameras) were temporarily installed on the ground, on rooftops, or on vehicles to detect chemical accidents from a distance, but one detection result alone was insufficient to determine chemical accidents, and it was difficult to identify the detection trend. Thus, this study presents a practical system for monitoring chemical accidents.