Mapping and detection of hotspot sources from Industrial Area Heat (Iah) using aerial and satellite-based tir data in Pasir Gudang

Abstract

When assessing the state of the climate system, industrial area heat (IAH) is one of the most critical variables for energy auditing. Thermal infrared (TIR) remote sensing techniques were used to track the surface temperature and microclimate impacts in an industrial environment by analysing in-situ data and their relationship with industrial features to characterise their impacts on human health and climate change. Based on TIR data, this study used an automatic detection method for industrial area heat (IAH). The IAH data is first retrieved, then the local abnormal high-temperature pixels are extracted using PIX4D software for UAV and split window for Landsat 8, and finally, the hotspot targets are identified using the spatial autocorrelation Moran's analysis tool available in the ArcGIS ESRI environment. The correlations (R2) between in-situ measurement and satellite-based industrial emissions at PGI were 0.85 with an RMSE of + 3.37 and 0.89 with an RMSE of + 1.42 at KSM. The detection accuracy of IAH methods is dominant. IAH accounted for 20% of the cool- and hot spots areas in the entire study area. The total cool-spots had a higher polygons per km2 (3.5 n/km2) value than the total hot-spots (0.6 n/km2) value, while LEVEL-3 and LEVEL-2 had the lowest values, while the highest values were always found in LEVEL-1, with approximately 50 % IAH variation between the previous and next level. Moving from the total average cool-spot to the total average hot-spot classes generally increased about 5 °C. Between the most extreme cool- and hot-spot levels (LEVEL-3) for PG in the overall industrial area, a mean IAH increase of approximately 34.7 °C and 58.5 °C was observed.