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

Author(s):  
M Z Dahiru ◽  
Mazlan Hashim
2018 ◽  
Vol 7 (4.20) ◽  
pp. 608 ◽  
Author(s):  
Muhammad Mejbel Salih ◽  
Oday Zakariya Jasim ◽  
Khalid I. Hassoon ◽  
Aysar Jameel Abdalkadhum

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.   


2015 ◽  
Vol 7 (4) ◽  
pp. 4268-4289 ◽  
Author(s):  
Fei Wang ◽  
Zhihao Qin ◽  
Caiying Song ◽  
Lili Tu ◽  
Arnon Karnieli ◽  
...  

Author(s):  
Ibra Lebbe Mohamed Zahir

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.


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

2014 ◽  
Vol 11 (10) ◽  
pp. 1840-1843 ◽  
Author(s):  
Juan C. Jimenez-Munoz ◽  
Jose A. Sobrino ◽  
Drazen Skokovic ◽  
Cristian Mattar ◽  
Jordi Cristobal

2019 ◽  
Vol 15 (2) ◽  
pp. 182-184
Author(s):  
Joko Sampurno ◽  
Apriansyah Apriansyah ◽  
Riza Adriat

In this research, models of heat distribution of the subsurface of the Wapsalit geothermal area were built, which their structures were known before, using finite different method. Rock thermal diffusivity was used as the model parameter, which controlled the heat flow. The result showed that the heat flow was adjusted the model parameters effectively. Land surface temperature (LST) as the result of the model was compared to LST from Landsat-8 Thermal Infrared Sensor Imagery and produced absolute error 6.8% and 3.6% for cross-section 1 and 2, respectively. This error percentage confirmed that the model was successfully depicted the actual heat distribution of the subsurface of the study area.


Author(s):  
F. Farhanj ◽  
M. Akhoondzadeh

Land surface temperature image is an important product in many lithosphere and atmosphere applications. This image is retrieved from the thermal infrared bands. These bands have lower spatial resolution than the visible and near infrared data. Therefore, the details of temperature variation can't be clearly identified in land surface temperature images. The aim of this study is to enhance spatial information in thermal infrared bands. Image fusion is one of the efficient methods that are employed to enhance spatial resolution of the thermal bands by fusing these data with high spatial resolution visible bands. Multi-resolution analysis is an effective pixel level image fusion approach. In this paper, we use contourlet, non-subsampled contourlet and sharp frequency localization contourlet transform in fusion due to their advantages, high directionality and anisotropy. The absolute average difference and RMSE values show that with small distortion in the thermal content, the spatial information of the thermal infrared and the land surface temperature images is enhanced.


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