Pipeline leakage detection for district heating systems using multisource data in mid- and high-latitude regions

In mid- and high-latitude regions, district heating systems (DHSs) are major heat supply solutions to both local industry and citizens. Pipeline leakage detection is therefore important for monitoring the condition of DHSs and promoting energy efficiency. In this paper, a saliency analysis method is presented for DHS pipeline leakage detection using remotely sensed infrared imagery, visible imagery, and geographic information system (GIS) data. In the saliency-based DHS leakage detection method, the infrared saliency map is created to enhance the leakage targets, and the pipeline location information extracted from the GIS data or the visible imagery acts as a distribution prior to reject false alarms. Finally, adaptive target segmentation by maximum entropy permits the automatic detection of potential leakage targets in the final fused saliency map. The approach was validated on three data sets acquired in Gavle in Sweden and Datong in China, with the heating leakages indicated by human analysts and field validation. The leakage detection accuracy of the new approach with a reduced false alarm rate is better than the previous methods. The results suggest that the proposed approach for DHS leakage detection from remotely sensed thermal infrared data has great potential for monitoring DHS conditions in mid and high-latitude regions.