A New Detection Method for Land Surface Anomalies From the Perspective of Thermal Infrared Remote Sensing

On-orbit rapid detection of land surface anomalies is important for ensuring ecological security and human safety. Land surface anomalies (e.g., fire, industrial heat source, and deforestation, etc.) are often accompanied by different degrees of thermal anomalies. Existing methods for detecting thermal anomalies have focused primarily on high-temperature anomalies, without available approach for detecting widespread low-temperature anomalies. Here, a Novel Method based on Constructed Reference land surface temperatures (LST) for on-orbit remote sensing detection of various Thermal Anomalies (NMCRTA) is proposed and further evaluated using Landsat 8 LST product. In this method, we first construct an fitted reference temperature based on LST spatiotemporal trend surface modeling and a real reference temperature based on contextual averaging. Then, the difference (including the step of removing atmospheric effects) between on-orbit observed LST and fitted reference LST, and the difference between on-orbit observed LST and real reference LST are calculated, respectively. Finally, these two temperature differences are utilized to detect thermal anomalies using corresponding thresholds. The results indicate that the NMCRTA can effectively detect deforestation, newly constructed buildings, and river drying, with an overall F1-score of 0.867, in a 100 × 100 km region scale. Meanwhile, the NMCRTA exhibited excellent accuracy in detecting fires, deforestation, and landslides at the 15 × 15 km scene scale, achieving F1-scores of 0.943, 0.857, and 0.791, respectively. Furthermore, the NMCRTA can continuously capture different thermal anomaly events associated with a newly constructed industrial heat source and perform well in nighttime. The NMCRTA is promising for future on-orbit remote sensing detection of various land surface anomalies, as a valuable supplement to optical on-orbit detection method.