scholarly journals Heat distribution modeling of the subsurface of Wapsalit geothermal area based on land surface temperature from Landsat-8 thermal infrared sensor imagery

2019 ◽  
Vol 15 (2) ◽  
pp. 182-184
Author(s):  
Joko Sampurno ◽  
Apriansyah Apriansyah ◽  
Riza Adriat
Keyword(s):  
Heat Flow ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Model Parameters ◽  
Landsat 8 ◽  
Heat Distribution ◽  
Geothermal Area ◽  
Infrared Sensor

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.

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

2018 ◽  
Vol 7 (4.20) ◽  
pp. 608 ◽  
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.   

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

2015 ◽  
Vol 7 (4) ◽  
pp. 4268-4289 ◽  
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

Land Surface Temperature Retrieval Methods From Landsat-8 Thermal Infrared Sensor Data

2014 ◽  
Vol 11 (10) ◽  
pp. 1840-1843 ◽  
Author(s):  
Juan C. Jimenez-Munoz ◽  
Jose A. Sobrino ◽  
Drazen Skokovic ◽  
Cristian Mattar ◽  
Jordi Cristobal
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Infrared ◽  
Sensor Data ◽  
Landsat 8 ◽  
Infrared Sensor ◽  
Temperature Retrieval

scholarly journals Geospatial Monitoring on Land Surface Temperature and Vegetation Dynamics: A Case of a City Area in Khulna, Bangladesh

2020 ◽  
Vol 3 (2) ◽  
pp. a35-43
Author(s):  
MD. NAZMUL HAQUE ◽  
NOWRIN RAHMAN KHANAM ◽  
MEHNAZ NANJIBA
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Landsat 8 ◽  
Environmental Condition ◽  
Infrared Sensor ◽  
The Third ◽  
Canopy Area

Land surface temperature and vegetation cover are two important parameters to evaluate the climate change and environmental condition. The current study is carried out in respect of monitoring the changing phenomena of climate and environment. The area selected to conduct the study was ward number 1, 2 and 3 of Khulna City Corporation), from the third largest city of Bangladesh. This study is corresponding through the calculation of Land Surface Temperature (LST) and Normalized Differential Vegetation Index (NDVI) for two different years, 2010 and 2018. LST and NDVI are observed to realize the association between surface temperature and amount of vegetation. With the help of ArcGIS 10.5, LST and NDVI calculations are done using Landsat 5 Thermal Mapper, Landsat 8 Operational Land Imager and Thermal Infrared Sensor images (for 2010 and 2018, respectively) collected from USGS Earth Explorer. The findings of the study specify that the highest temperature in 2018 is 32.5˚C in ward 2 and in 2010 it was 27.5˚C in ward 3, though the overall vegetation amount decreased in 2018, About 18, 900 square meter of very low canopy area has increased in ward 3 from the period of 2010 to 2018 and in the same time 35, 100 square meter of low canopy area has been decreased for the overall study area. However, parts of the study area of ward no. 3 had faced a significant increase in vegetation cover which is the cause of low temperature compared to ward 1 and 2 in 2018.

scholarly journals 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

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.

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

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

scholarly journals SPATIAL AND TEMPORAL VARIABILITY OF SURFACE TEMPERATURE, LAND USE AND LAND COVER CHANGE: A CASE STUDY IN CAMPINAS, BRAZIL

2021 ◽  
Vol 28 ◽  
Author(s):  
Luiza Marchezan Bezerra ◽  
Ana Maria Heuminski de Avila
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface ◽  
Land Use Changes ◽  
Thermal Infrared ◽  
Climatic Conditions ◽  
Spatial And Temporal Variability ◽  
Landsat 8 ◽  
Climatic Data ◽  
Infrared Sensor

deteriorating climatic conditions in urban centers of Brazil is a real concern for human security and urban livelihood sustainability.  The city of Campinas in São Paulo state/Brazil is highly vulnerable to climatic disasters. The present paper analyses the relationship between land use changes and temperature in Campinas between 1989 and 2016. The 28-year period was chosen due to the variability of climatic data in three meteorological stations (University of Campinas, Agronomic Institute of Campinas and International Airport of Viracopos). Data from five sources were used for land use land changes (LULC), and land surface temperature (LST) analysis. The data sources were: i) Landsat 5 Thermometer Mapper (TM), ii) Landsat 5 Thermal Infrared Sensor (TIRS), iii) Thermal Infrared Sensor (ETM +) sensors from Landsat 5, iv) Landsat 8 Operational Land Imager (OLI), and v) Thermal Infrared Sensor (TIRS). The results indicate consistent relations between urbanized increase area and the elevation of air and surface temperature in Campinas. In the studied period, there was an increase of 23% in urbanized areas in Campinas and around the meteorological stations. Cepagri presented the highest growth, about 22%, as well as the station with the highest air temperature

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