LAND SURFACE TEMPERATURE (LST) ESTIMATION AT KUSHTIA DISTRICT, BANGLADESH

Land Surface Temperature (LST) is a key phenomenon in worldwide climate change. The knowledge of surface temperature is important to a range of issues and themes in earth sciences, central to urban climatology, global environmental change, and human-environment interactions. In this study, LST for Kushtia District, Khulna division, Bangladesh, is derived using Arc-GIS software version from the images of Landsat 8 Optical Land Imager (OLI) of 30 m resolution and Thermal Infrared Sensor (TIR) data of 100 m resolution, Landsat-7 Enhanced Thematic Mapper plus (ETM+) with opto-mechanical sensor and Spatial Resolution of 30 m (60 m – thermal, 15-m panchromatic) and Landsat-5 Thematic MAPPER (TM) satellites. A total time span of 20 years, starting from 1998 to 2018 is selected. At every 5 years interval starting from 1998, air temperature, LST, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) have been calculated. Using the equation from Landsat user’s handbook, the digital number of thermal infrared band is converted into spectral radiance. Plank’s Inverse Function is used to obtain the effective at-sensor brightness temperature from the spectral radiance. The surface emissivity based on NDVI classes is used to retrieve the final LST. The study reveals that LST is increasing with the passage of time. Maximum values of LST are found along the North-East and North-West regions of Kushtia district. NDVI is found to have positive correlation with LST. Also, it has been found that NDWI has little influence on LST. The reasons behind the rise and fall of LST in different years are explained from changes in total vegetation coverage and total abundance of water body coverage viewpoint. The spatial distribution figures of air temperature, LST, NDVI and NDWI could be used as a guideline for urban planning, strategies for quality improvement of urban environment and a smart solution to the reduction of LST.

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Estimation and Validation of Land Surface Temperature by using Remote Sensing & GIS for Chittoor District, Andhra Pradesh

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i5.1059 ◽

2021 ◽

Vol 12 (5) ◽

pp. 607-617

Author(s):

A. Rajani, Dr. S.Varadarajan

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Andhra Pradesh ◽

Temperature Data ◽

Sensor Data ◽

Spectral Radiance ◽

Landsat 8 ◽

Thermal Band

Land Surface Temperature (LST) quantification is needed in various applications like temporal analysis, identification of global warming, land use or land cover, water management, soil moisture estimation and natural disasters. The objective of this study is estimation as well as validation of temperature data at 14 Automatic Weather Stations (AWS) in Chittoor District of Andhra Pradesh with LST extracted by using remote sensing as well as Geographic Information System (GIS). Satellite data considered for estimation purpose is LANDSAT 8. Sensor data used for assessment of LST are OLI (Operational Land Imager) and TIR (Thermal Infrared). Thermal band contains spectral bands of 10 and 11 were considered for evaluating LST independently by using algorithm called Mono Window Algorithm (MWA). Land Surface Emissivity (LSE) is the vital parameter for calculating LST. The LSE estimation requires NDVI (Normalized Difference Vegetation Index) which is computed by using Band 4 (visible Red band) and band 5 (Near-Infra Red band) spectral radiance bands. Thermal band images having wavelength 11.2 µm and 12.5 µm of 30th May, 2015 and 21st October, 2015 were processed for the analysis of LST. Later on validation of estimated LST through in-suite temperature data obtained from 14 AWS stations in Chittoor district was carried out. The end results showed that, the LST retrieved by using proposed method achieved 5 per cent greater correlation coefficient (r) compared to LST retrieved by using existing method which is based on band 10.

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Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.20.27402 ◽

2018 ◽

Vol 7 (4.20) ◽

pp. 608 ◽

Cited By ~ 3

Author(s):

Muhammad Mejbel Salih ◽

Oday Zakariya Jasim ◽

Khalid I. Hassoon ◽

Aysar Jameel Abdalkadhum

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Thermal Infrared ◽

Landsat 8 ◽

Infrared Sensor ◽

Infrared Thermometer ◽

Ground Truth Data ◽

Land Cover Types

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 differences in land cover and compare the relationship between land surface temperature and land cover types.

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

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/540/1/012059 ◽

2020 ◽

Vol 540 ◽

pp. 012059

Author(s):

M Z Dahiru ◽

Mazlan Hashim

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Thermal Infrared ◽

Industrial Area ◽

Landsat 8 ◽

Infrared Sensors

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An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data

Remote Sensing ◽

10.3390/rs70404268 ◽

2015 ◽

Vol 7 (4) ◽

pp. 4268-4289 ◽

Cited By ~ 130

Author(s):

Fei Wang ◽

Zhihao Qin ◽

Caiying Song ◽

Lili Tu ◽

Arnon Karnieli ◽

...

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Thermal Infrared ◽

Sensor Data ◽

Landsat 8 ◽

Infrared Sensor ◽

Temperature Retrieval

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Application of Geo-informatics Technology to Access the Surface Temperature Using LANDSAT 8 OLI/TIRS Satellite Data: A Case Study in Ampara District in Sri Lanka

10.20944/preprints202009.0289.v1 ◽

2020 ◽

Author(s):

Ibra Lebbe Mohamed Zahir

Keyword(s):

Sri Lanka ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Thermal Infrared ◽

Landsat 8 ◽

Surface Emissivity ◽

Land Surface Emissivity

Land Surface Temperature is a one of the key variable of Global climate changes and model which estimate radiating budget in heat balance as control of climate model. It is a major influenced factor by the ability of the surface emissivity. In this study, were used Landsat 8 satellite image that have Operational Land Imager and Thermal Infrared Sensor to calculate Land Surface Temperature through geospatial technology over Ampara district, Sri Lanka. The Land Surface Temperature was estimated with respect to Land Surface Emissivity and Normalized Difference Vegetation Index values determined from the Red and Near Infrared channels. Land Surface Emissivity was processed directly by the thermal Infrared bands. Pixels based calculation were used to effort at LANDSAT 8 images that thermal Band 10 various dates in this study. The results were achievable to compute Normalized Difference Vegetation Index, Land Surface Emissivity, and Land Surface Temperature with applicable manner to compare with land use/ land cover data. It determines and predicts the changes of surface temperature to favorable to decision making process for the society. Study area faces seasonal drought in Sri Lanka, the prediction method that how land can be efficiently used with the present condition. Therefore, the Land Surface Temperature estimation can prove whether new irrigation systems for agricultural activities or can transformed source of energy into useful form that introducing solar hubs for energy production in future.

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Estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

Advances in Remote Sensing ◽

10.4236/ars.2021.104009 ◽

2021 ◽

Vol 10 (04) ◽

pp. 131-149

Author(s):

Yaw A. Twumasi ◽

Edmund C. Merem ◽

John B. Namwamba ◽

Olipa S. Mwakimi ◽

Tomas Ayala-Silva ◽

...

Keyword(s):

Comparative Analysis ◽

Surface Temperature ◽

Land Surface Temperature ◽

Satellite Data ◽

Land Surface ◽

Thermal Infrared ◽

Landsat 8 ◽

Landsat 8 Oli ◽

Two Cities

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Retrieval of Land Surface Temperature of Lahore Through Landsat-8 TIRS Data

International Journal of Economic and Environmental Geology ◽

10.46660/ojs.v10i1.220 ◽

2019 ◽

Vol 10 (1) ◽

pp. 70-77

Author(s):

Muhammad Nasar -u-Minallah

Keyword(s):

Radiative Transfer ◽

Surface Temperature ◽

Land Surface Temperature ◽

Vegetation Cover ◽

Land Surface ◽

Global Climate ◽

Spectral Radiance ◽

Landsat 8 ◽

Barren Land ◽

Data Continuity

Land surface temperature (LST) is an important parameter in global climate change and urban thermalenvironmental studies. The significance of land surface temperature is being acknowledged gradually and interest isincreasing in developing methodologies for the retrieval of LST from Satellite Remote Sensing (SRS) data. ThermalInfrared Sensor (TIRS) of Landsat-8 is the newest TIR sensor for the Landsat Data Continuity Mission (LDCM),offering two adjacent thermal infrared bands (10, 11), having significant beneficiary for the land surface temperatureinversion. The spectral radiance can be estimated through TIR bands 10 and 11 of Landsat-8 OLI_TIRS satellite image.In the present study, the radiative transfer equation-based method has been employed in estimating LST of Lahore andthe analysis demonstrated that estimated LST has the highest accuracy from the radiative transfer method through band10. Land Surface Emissivity (LSE) was derived with the aid of the NDVI’s threshold technique. The present studyresults show that as the built-up area increases and vegetation cover decreases in urban surface, they are linked toincrease in urban land surface temperature and conversely larger vegetation cover associated with lower urbantemperature. The output exposed that LST was high in built-up and barren land, whereas it was low in the area wherethere were more vegetation cover and water.

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