The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLVI-4/W3-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W3-2021, 87–102, 2022
https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-87-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W3-2021, 87–102, 2022
https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-87-2022
 
10 Jan 2022
10 Jan 2022

SHARPENING OF THERMAL SATELLITE IMAGERY FROM KLANG INDUSTRIAL AREA IN PENINSULAR MALAYSIA USING THE TSHARP APPROACH

M. Z. Dahiru1,2,3, M. Hashim1,2, and N. Hassan1,2 M. Z. Dahiru et al.
  • 1Geoscience & Digital Earth Centre (INSTEG), Research Institute for Sustainable Environment (RISE), Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • 2Faculty of Geoinformation & Real Estate, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  • 3Adamawa State Polytechnic, Yola, Adamawa State, Nigeria

Keywords: Remote sensing, Heat emission, downscaling, split-window algorithm, Indicators (NDVI, NSVI and NDBI)

Abstract. Measuring high spatial/temporal industrial heat emission (IHE) is an important step in industrial climate studies. The availability of MODIS data products provides up endless possibilities for both large-area and long-term study. nevertheless, inadequate for monitoring industrial areas. Thus, Thermal sharpening is a common method for obtaining thermal images with higher spatial resolution regularly. In this study, the efficiency of the TsHARP technique for improving the low resolution of the MODIS data product was investigated using Landsat-8 TIR images over the Klang Industrial area in Peninsular Malaysia (PM). When compared to UAV TIR fine thermal images, sharpening resulted in mean absolute differences of about 25 °C, with discrepancies increasing as the difference between the ambient and target resolutions increased. To estimate IHE, the related factors (normalized) industrial area index as NDBI, NDSI, and NDVI were examined. The results indicate that IHE has a substantial positive correlation with NDBI and NDSI (R2 = 0.88 and 0.95, respectively), but IHE and NDVI have a strong negative correlation (R2 = 0.87). The results showed that MODIS LST at 1000 m resolution can be improved to 100 m with a significant correlation R2 = 0.84 and RMSE of 2.38 °C using Landsat 8 TIR images at 30 m, and MODIS LST at 1000 m resolution can still be improved to 100 m with significant correlation R2 = 0.89 and RMSE of 2.06 °C using aggregated Landsat-8 TIR at 100 m resolution. Similarly, Landsat-8 TIR at 100 m resolution was still improved to 30 m and used with aggregate UAV TIR at 5 m resolution with a significant correlation R2 = 0.92 and RMSE of 1.38 °C. Variation has been proven to have a significant impact on the accuracy of the model used. This result is consistent with earlier studies that utilized NDBI as a downscaling factor in addition to NDVI and other spectral indices and achieved lower RMSE than techniques that simply used NDVI. As a result, it is suggested that the derived IHE map is suitable for analyzing industrial thermal environments at 1:10,000 50,000 scales, and may therefore be used to assess the environmental effect.