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Land Surface Temperature (LST) can be calculated through a thermal infrared remote sensing data. It can record the apparent temperature of the Earth's surface by measuring the radiant energy exiting its surface. With the advent of satellite images and digital image processing software, now it is possible to calculate LST. In this study, LST for Devikulam taluk was derived using Single Window algorithm (SW) with the use of Landsat-8 (Path-144 and Row-53) Thermal Infrared Sensor (TIRS) data of 100m resolution. Emissivity was derived with the help of NDVI proportion of vegetation technique for which Operational Land Imager (OLI) bands 4 and 5 (30 m resolution) were used. The results showed that surface temperature was high in the barren regions whereas it was low in the thick vegetation cover regions. As the SW algorithm uses both OLI and TIRS bands, the LST derived using them were more reliable and accurate.
International Journal of Advance Research Ideas and Innovations in Technology
Estimation of Land Surface Temperature using LANDSAT DATA: A case study of Agra city, IndiaLand Surface Temperature (LST) is an important indicator for the study of climate change, urban environment, heat balance studies, hydrological and agricultural process, and urban land use and land cover as well as user input for climate models. LANDSAT data is utilized for the number of applications such as environment study, digester and resource management. This study has been made to estimate, LST using Arc GIS over Agra, India, using LANDSAT 8 and 5 satellite data. The LST has been estimated with respect to Normalized Difference Vegetation Index (NDVI) values determined from the Red and Near Infrared bands. The Land Surface Emissivity (LSE) is retrieved directly from the Thermal Infrared bands. The present study focuses on ArcGIS Raster functions and Raster calculation using the thermal band 10 and 11 of Landsat 8 satellite and thermal band 6 of Landsat 5 on the month of April. The results are feasible to calculate NDVI, LSE, and LST with appropriate accuracy. In the last drive out the temperature variance in different land use and land cover area of Agra city, India.
L and surface temperature (LST) is very important environmental parameter to be studied. The meaning of land surface temperature is the temperature of earth surface when we directly contact with it. It is also called skin temperature of the earth surface. LST is one of the important factors in global ABSTRACT : To estimate land surface temperature (LST) has an important role for agriculture as well as global change of climate, growth of vegetation and glacier melting. It combines the results of all surface atmosphere interactions and energy fluxes between the surface and the atmosphere. Now-a-days, estimation of temperature of land surface is being calculated with the help of satellite images containing thermal infrared band. Though land surface temperature derived from satellite, could be a beneficial complement to conventional land surface temperature data sources. This research, proposed a methodology for determining land surface temperature through using a structured mathematical algorithm viz., split window (SW) algorithm. Split window algorithm has been used on LANDSAT 8 with operational land imager i.e. OLI sensor and thermal infrared sensor i.e. TIRS dataset of Udham Singh Nagar district. TIRS shows two thermal bands i.e. band 10 and band 11. SW approach requires brightness temperature value of both band 10 and band 11 as well as land surface emissivity which is calculated from OLI bands i.e. NIR and Red, for the estimation of land surface temperature. The spectral radiance was determined using thermal infrared bands i.e. band 10 and band 11. Emissivity was calculated by using normalized difference vegetation index i.e. NDVI threshold technique for which OLI bands 2, 3, 4 and 5 were utilized. SW approach uses brightness temperature of two bands of thermal infrared, mean and difference in land surface emissivity for estimating land surface temperature. In this paper, 6 Dec. 2015 date was selected as an example to show the approach of using SW technique to estimate the LST of Udham Singh Nagar district of Uttarakhand state in India.
International Journal of Applied Research
Estimating land surface temperature in ArcGIS using Landsat-8, Hoshangabad district, (Madhya Pradesh)2017 •
2022 •
Urban sprawl has led to a decline in the agricultural land and rise in the congested built-up area in all the developing countries while increasing the temperature of the urban atmosphere. Rising temperature has slowly started risking human and plant health. By using Landsat 8 (Operational Land Imager) OLI/ (Thermal Infrared Sensor) TIRS thermal bands 10 and 11 the Land Surface Temperature (LST) was measured as it is considered an important aspect of land environment because it measures the emission of heat radiance from the surface of the earth and heats up several features of the earth. The satellite data of the Gorakhpur City, Uttar Pradesh was taken at the peak summer time and the data included was from the month of May,2013,2016 and 2019 respectively to measure the rise in Land Surface Temperature from 17.34 C (2013) to 20.785 C (2019). Vegetation cover has a significant effect on LST because it lowered down from 0.345(2013) to 0.171 (2019) showed an inverse relationship The data obtained was co-related with Land Surface Temperature (LST) and the greenery of the area or Normalized Differential Vegetation Index (NDVI). The Correlation coefficient obtained was~-0.8 which indicated that surface temperature of the land increases with the decrease in the vegetation cover forming a strong negative co-relation. This study showed the relationship between rise in land temperature with the decrease in the vegetation cover.
Earth Science Informatics
Correlation analysis of land surface temperature on landsat-8 data of Visakhapatnam Urban Area, Andhra Pradesh, India2022 •
International Journal of Engineering & Technology
Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera2018 •
This paper illustrates a proposed method for the retrieval of land surface temperature (LST) from the two thermal bands of the LANDSAT- 8 data. LANDSAT-8, the latest satellite from Landsat series, launched on 11 February 2013, using LANDSAT-8 Operational Line Imager and Thermal Infrared Sensor (OLI & TIRS) satellite data. LANDSAT-8 medium spatial resolution multispectral imagery presents particular interest in extracting land cover, because of the fine spectral resolution, the radiometric quantization of 12 bits. In this search a trial has been made to estimate LST over Al-Hashimiya district, south of Babylon province, middle of Iraq. Two dates images acquired on 2nd &18th of March 2018 to retrieve LST and compare them with ground truth data from infrared thermometer camera (all the measurements contacted with target by using type-k thermocouple) at the same time of images capture. The results showed that the rivers had a higher LST which is different to the other land cover types, of less than 3.47 C ◦, and the LST different for vegetation and residential area were less than 0.4 C ◦ with correlation coefficient of the two bands 10 and 11 Rbnad10= 0.70, Rband11 = 0.89 respectively, for the imaged acquired on the 2nd of march 2018 and Rband10= 0.70 and Rband11 = 0.72 on the 18th of march 2018. These results confirm that the proposed approach is effective for the retrieval of LST from the LANDSAT-8 Thermal bands, and the IR thermometer camera data which is an effective way to validate and improve the performance of LST retrieval. Generally the results show that the closer measurement taken from the scene center time, a better quality to classify the land cover. The purpose of this study is to assess the use of LANDSAT-8 data to specify temperature differ- ences in land cover and compare the relationship between land surface temperature and land cover types.
2021 •
Land Surface Temperature (LST) is average temperature of an element of the exact surface of the Earth calculated from measured radiance which depends on the albedo, the vegetation cover, and the soil moisture. Land Surface Temperature can affect human discomfort, health problem, higher energy bill and further reduce the habitability of urban and sub urban area as Makassar city has been recently undergoing massive urban development. This study tries to monitor and estimate Land Surface Temperature by using Landsat 8 TIRS and the data analyzed by vegetation index, and temperature index in order to derive Land Surface Temperature value. The result shows that the vegetation area declined around 3470 hectares in the last four years while the urban area increased approximately 1509 hectare. In addition, 2015, Makassar, South Sulawesi, Indonesia are experienced the highest temperature at 32 degree Celsius while 2019 shown that the maximum heat reached 29 degree celsius. However, the moder...
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Liberal Arts and Social Sciences International Journal (LASSIJ)
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