Abstract
Land surface temperature is an important factor in many areas, such as global climate change, hydrological, geo-/biophysical, and urban land use/land cover. As the latest launched satellite from the LANDSAT family, LANDSAT 8 has opened new possibilities for understanding the events on the Earth with remote sensing. This study presents an algorithm for the automatic mapping of land surface temperature from LANDSAT 8 data. The tool was developed using the LANDSAT 8 thermal infrared sensor Band 10 data. Different methods and formulas were used in the algorithm that successfully retrieves the land surface temperature to help us study the thermal environment of the ground surface. To verify the algorithm, the land surface temperature and the near-air temperature were compared. The results showed that, for the first case, the standard deviation was 2.4°C, and for the second case, it was 2.7°C. For future studies, the tool should be refined within situmeasurements of land surface temperature.
Highlights
Land surface temperature (LST) is defined as the temperature felt when the land surface is touched with the hands or the skin temperature of the ground [1]
LST is an important factor in many areas of studies, such as global climate change, hydrological and agricultural processes, and urban land use/land cover
After the digital numbers (DNs) are converted to reflection, the TIRS band data should be converted from spectral radiance to brightness temperature (BT) using the thermal constants provided in the metadata file
Summary
Land surface temperature (LST) is defined as the temperature felt when the land surface is touched with the hands or the skin temperature of the ground [1]. LST is an important factor in many areas of studies, such as global climate change, hydrological and agricultural processes, and urban land use/land cover. Calculating LST from remote sensed images is needed since it is an important factor controlling most physical, chemical, and biological processes of the Earth [2]. The algorithm introduced in this paper has been developed using ERDAS IMAGINE 2014, with the Model Maker allowing us to create a model that will repeat the process automatically, and it is easy to develop a simple tool useful for doing pixel calculations. The tool presented in this paper is used for calculating the LST of a given LANDSAT 8 image with the input of the fourth (red wavelength/micrometres, 0.64–0.67), fifth (near infrared (NIR) wavelength/micrometres, 0.85–0.88), and tenth (thermal infrared sensor (TIRS) wavelength/micrometres, 10.60– 11.19) bands. Following January 6, 2014, recommendations of USGS of not using TIRS Band 11 due to its larger calibration uncertainty, only Band 10 was included in the algorithm
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