An Approach for the Retrieval of Land Surface Temperature from the Industrial Area Using Landsat-8 Thermal Infrared Sensors

Abstract

The thermal imagine provides data with synoptic coverage for investigating thermal information from hot sources for detecting, mapping energy loss from the industrial area. This study attempts to retrieved heat loss from the industrial area using Landsat-8 TIRS experimented at an industrial area of Pasir Gudang, Peninsular Malaysia, the main objective is to investigate the sensitivity of Landsat-8 TIR for detecting industrial thermal energy within the various range of targets of different temperatures. An estimated heat map with absolute surface temperature values is the final output. Apart of the pre-processing of Landsat-8 TIRS data, data are processed for the retrieval of land surface temperature, then subjected to a downscaling process to final 30 x 30 m pixels, hence enable to merge with all Landsat-8 bands for visualization and validation of results. The split window algorithm (SWA) is used for the temperature retrieval from band 10 and 11, with other driven parameters. The Multiple Adaptive Regression Splines (MARS) model for spatial downscaling was adopted in this study. The generated thermal energy map was then validated over selected targets in the field and compared to corresponding downscaled MODIS LST product (MODIS11A2). TIR bands applied with SWA generated 13.7°C temperature dynamic range from 22.35˜51.36° C in comparison with MODIS LST product values range from 27.17 ˜ 37.65°C). Results indicated good agreement between the generated thermal energy map with the in-situ validations (RMSE=0.43 °C). It is therefore concluded that derived Land surface temperature map derived is suitable for study industrial thermal environment at 1:50,000 ˜ 100,000 scales, adequately to be used for environmental impact assessment.

An Observation Study for Cold and Freezing Injury of Sugarcane Based on China Meteorological Administration Land Data Assimilation System, CLDAS Temperature Data

“…Moderate-resolution Imaging Spectroscopy using (MODIS) remote sensing data has been more widely used in the monitoring and evaluation of chilling and freezing damage of sugarcane (Tan et al, 2008;Nihar et al, 2022). The monitoring models used are mainly the vegetation condition index (Thavorntam et al, 2023;Touhami et al, 2022), vegetation index difference (Kasimati et al, 2022;Weiss et al, 2020;Wang et al, 2020;Qian et al, 2019), surface reflectance (Li et al, 2022;Sun and Ming, 2019) and the ground temperature inversion of ground sensor data (Li et al, 2022;Sun and Ming, 2019;Dahiru and Hashim, 2020). However, the weather and topographic features are complex and diverse in Guangxi.…”

Sharpening of Thermal Satellite Imagery From Klang Industrial Area in Peninsular Malaysia Using the Tsharp Approach

“…Therefore, we undertake to use MARS in heat emission downscaling for the industrial area of Pasir Gudang. The objectives of this study present as follow; (i) To explore the techniques for downscaling spatial resolution images for both UAV and Landsat-8 TIRS for enhancing the accuracy of the downscaled map (ii) to investigate the sensitivity of Landsat-8 TIR for detecting industrial thermal energy heat emission within various range of targets for different temperatures (iii) and to evaluate the link between the industrial material and thermal energy at microscales (1:10,000 ~ 50,000 scales) (Burdun et al, 2019;Dahiru and Hashim, 2020). Therefore, the potential of the Multivariate Adaptive Regression Splines model is suitable for study industrial thermal energy for impact assessment.…”