The monitoring of iron and steel enterprises through manual field supervision is time-consuming and labor-intensive. To address this problem, this study proposed identifying the high-temperature anomalous areas based on satellite-carried thermal infrared sensors. Then, based on conventional remote sensing interpretation combined with thermal infrared anomaly monitoring and the quasi-synchronous data of March to May in the first quarter, as well as the scope of existing iron and steel enterprises and high-resolution images of the same period, this study extracted information on suspected iron and steel enterprises/low-quality steel enterprises according to the thermal infrared threshold and the thermal anomaly distribution. Subsequently, interpretation symbols were constructed according to the medium- to high-resolution digital orthophoto maps (DOMs), and anomaly areas were identified by overlapping the map spots of existing iron and steel enterprises/low-quality steel enterprises. Finally, the monitoring results of the new method were tested using existing project results, forming the monitoring comparison results of steel overcapacity cutting. As a result, the comprehensive detection accuracy was 88.15%. The results of this study show that the Landsat8 data with a thermal infrared band of 10.6~11.19 μm can effectively monitor the high-temperature anomalies of iron and steel enterprises. Therefore, this band can be selected for future thermal anomaly monitoring based on thermal infrared remote sensing. This study is designed to explore more extensive data sources for monitoring steel overcapacity cutting and to provide approaches to solve the possible data bottlenecks and emergency monitoring problems. It can be used as a reference for guiding both project production and remote sensing monitoring of steel overcapacity cutting.