scholarly journals LEAST SQUARE APPROACH FOR ESTIMATING OF LAND SURFACE TEMPERATURE FROM LANDSAT-8 SATELLITE DATA USING RADIATIVE TRANSFER EQUATION

Author(s):  
Y. Jouybari-Moghaddam ◽  
M. R. Saradjian ◽  
A. M. Forati

Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Pâmela Suélen Käfer

ABSTRACT. Land surface temperature (LST) is an important parameter in the investigation of environmental and climatic changes at various scales. However, estimating this parameter from the radiation emitted in the thermal infrared (TIR) region is a difficult task because the radiation measured by the satellite sensors is strongly affected by atmospheric effects. All LST retrieval methods require validation with field measurements. Nonetheless, the validation of this type of data is a challenge because the LST changes rapidly in time and the measurements must be performed together with the sensor overpass. In addition, most methodologies are developed and tested focusing on the Northern Hemisphere. Considering that operational ways of obtaining LST should be constantly investigated, the aim of this paper was to study the effect of the use of temperature-based laboratory measurements in the determination of the emissivity and LST retrieval from orbital remote sensing data. Moreover, it was intended to perform a comparative analysis among the most recent single-channel algorithms available on the literature, applied to band 10 (10.6-11.19 μm) of the Landsat 8 TIRS. The algorithms considered were: Single-Channel generalized (SC), Improved Single-channel (ISC) and Improved Mono-window (IMW). A field of coastal dunes was chosen as study area. Two sets of laboratory emissivity measurements were performed with field samples at different temperatures using a Fourier Transform Infrared (FT-IR). Emissivity and temperature data were obtained in the study area concomitantly with the satellite overpass. The Radiative Transfer Equation (RTE) with parameters of global atmospheric profiles was tested as a method of validation. A variation of approximately 2% in the emissivity in relation to the temperature was observed, which could be neglected. The FT-IR presents limitations on the period to acquire stability, however as long as this limitation is respected and the calibration approach correctly carried out, laboratory measurements can achieve optimum accuracy and replace field validation. Available spectral libraries of emissivity have also proved to be a good alternative. All evaluated single-channel methods are suitable for obtaining LST; however, ISC provided superior results in all analyzes, producing higher R² (0.99978) and lower RMSE (0.019) relative to the other algorithms tested.RECUPERAÇÃO DE TEMPERATURA DE SUPERFÍCIE TERRESTRE DA RADIÂNCIA TERMAL COLETADA PELO SENSOR TIRS/LANDSAT 8: APLICAÇÕES DE MEDIDAS DE CAMPO E LABORATÓRIO RESUMO. A temperatura da superfície terrestre (Land surface temperature - LST) é um importante parâmetro na investigação de mudanças ambientais e climáticas em várias escalas. Entretanto, estimar esse parâmetro da radiação emitida na região do infravermelho termal (TIR) é uma tarefa difícil, pois as radiações medidas pelos sensores dos satélites são fortemente afetadas por efeitos atmosféricos. Todos métodos de recuperação de LST requerem validação com medidas de campo. Porém, a validação deste tipo de dado é um desafio, visto que a LST muda rapidamente no tempo e as medidas devem ser realizadas em conjunto com a passagem do sensor. Além disso, a maioria das metodologias são desenvolvidas e testadas com foco no hemisfério norte. Tendo em vista que maneiras operacionais de se obter LST devem ser constantemente investigadas, o objetivo desta pesquisa foi estudar o efeito do uso de medidas de emissividade de laboratório tomadas com base em temperaturas na determinação da LST a partir de dados de sensoriamento remoto orbital. Ademais, pretendeu-se realizar uma análise comparativa entre os algoritmos single-channel mais recentes existentes na literatura, aplicados à banda 10 (10,6-11,19 μm) do Landsat 8 TIRS. Os algoritmos considerados foram: Single-Channel Generalizado (SCG), Improved Single-Channel (ISC) e Improved Mono-Window (IMW). Um campo de dunas costeiras foi escolhido como área de estudo. Dois conjuntos de medidas de emissividade de laboratório foram construídos com amostras de campo em diferentes temperaturas com uso de um Fourier Transform Infrared (FT-IR). Dados de emissividade e temperatura foram obtidos na área de estudo concomitamente com a passagem do sensor. A equação de transferência radiativa (Radiative Transfer Equation - RTE) com parâmetros de perfis atmosféricos globais foi testada como forma de validação de dados. Uma variação de aproximadamente 2% na emissividade em relação à temperatura foi observada, podendo ser negligenciada. O FT-IR apresenta limitações quanto ao período para adquirir estabilidade, porém respeitando esta limitação e realizando abordagem correta de calibração, medidas laboratoriais podem atingir ótima acurácia e substituir a validação de campo. Bibliotecas espectrais disponíveis de emissividade demonstraram ser também uma alternativa válida. Todos métodos Single-Channel avaliados são adequados para obter LST; no entanto, o ISC forneceu resultados superiores em todas as análises, produzindo maior R² (0,99978) e menor RMSE (0.019) em relação aos demais.


2021 ◽  
Vol 10 (04) ◽  
pp. 131-149
Author(s):  
Yaw A. Twumasi ◽  
Edmund C. Merem ◽  
John B. Namwamba ◽  
Olipa S. Mwakimi ◽  
Tomas Ayala-Silva ◽  
...  

2019 ◽  
Vol 10 (1) ◽  
pp. 70-77
Author(s):  
Muhammad Nasar -u-Minallah

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.


Author(s):  
Ravi Kumar ◽  
Anup Kumar

Land surface temperature (LST) represents hotness of the surface of the Earth at a particular location. Land surface temperature is useful for meteorological, climatological changes, heat island, agriculture, hydrological processes at local, regional and global scale. Presently many satellite sensor data are available for calculation of land surface temperature like Landsat 8 and MODIS. In the present study land surface temperature in Panchkula district of Haryana have been calculated using Landsat 8 satellite data of 5th May 2019 and 28th October 2019. Already available equations were used for computation of LST in the study area. LST in the study area varies from 18°C to 56°C. High LST is observed in cultivation land, urban area while low LST is observed in hilly forest area in the study area. In the study validation of LST could not be done because of not available of temperature data of studied dates, however, the result gives idea of land surface temperature on a particular day and location.


Author(s):  
Muhammad Nasar -u-Minallah

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.


2020 ◽  
Vol 223 ◽  
pp. 03011
Author(s):  
Elena A. Mamash ◽  
Igor A. Pestunov ◽  
Dmitri L. Chubarov

The paper discusses the applicability of Landsat 8 data for analyzing the land surface temperature distribution over the territory of Novosibirsk. The satellite data is compared with the data from ground meteorological stations. Using cloud-based systems and methods for processing time series of satellite data, a composite image of the temperature field for the territory of Novosibirsk is built; trends and anomalies in the temperature distribution in the urban area are studied. The results could be applied in urban development analysis and management of the city territory.


Sign in / Sign up

Export Citation Format

Share Document