Abstract
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.
Highlights
Heat loss is an important environmental variable and measure of air quality (Veefkind et al, 2007; Energy, 2008; Rani et al, 2018). the influence of energy loss in economic sectors and vigorous waste heat loss from industrial plants have substantial implications for human health and climate change (Vollrath, 1987)
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 Thermal infrared (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
The advancement in remote sensing technology offers an opportunity to provide a reliable, consistent, and repeatable approach within the working frame from local to a global scale, as well as long-term monitoring of oil spillage operations (Bromley et al, 2015; Casagli et al, 2017) The development and changes related to land cover and urban features have been associated with industrial heat emission, where the surface air temperature is becoming higher compared to the surrounding environment (Lee et al, 2003)
Summary
Heat loss is an important environmental variable and measure of air quality (Veefkind et al, 2007; Energy, 2008; Rani et al, 2018). the influence of energy loss in economic sectors and vigorous waste heat loss from industrial plants have substantial implications for human health and climate change (Vollrath, 1987). The influence of energy loss in economic sectors and vigorous waste heat loss from industrial plants have substantial implications for human health and climate change (Vollrath, 1987) Various phenomena such as urban up-to-date, forest fire, and more recently industrial related thermal objects have become issues of concern. The influence of energy loss in economic sectors and vigorous waste heat loss from industrial plants for many possible applications such as industrial inspection (Nikolic et al, 2013; Baena et al, 2017; Boesch, 2017), environmental monitoring (Turner et al, 2014; Chmaj and Selvaraj, 2015; Harvey et al, 2016; Torres-rua and Hipps, 2019), have substantial implications for human health and climate change (Vollath, 1987). There is a need for industrial heat regulations which will attach to green space to monitor the heat intensity from industrial heat emissions through a
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