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

机译:通过Landsat-8 TIRS数据反演拉合尔的地表温度

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Land surface temperature (LST) is an important parameter in global climate change and urban thermal environmental studies. The significance of land surface temperature is being acknowledged gradually and interest is increasing in developing methodologies for the retrieval of LST from Satellite Remote Sensing (SRS) data. Thermal Infrared 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 temperature inversion. 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 and the analysis demonstrated that estimated LST has the highest accuracy from the radiative transfer method through band 10. Land Surface Emissivity (LSE) was derived with the aid of the NDVI’s threshold technique. The present study results show that as the built-up area increases and vegetation cover decreases in urban surface, they are linked to increase in urban land surface temperature and conversely larger vegetation cover associated with lower urban temperature. The output exposed that LST was high in built-up and barren land, whereas it was low in the area where there were more vegetation cover and water.
机译:地表温度(LST)是全球气候变化和城市热环境研究的重要参数。人们逐渐认识到地表温度的重要性,并且对开发用于从卫星遥感(SRS)数据中检索LST的方法学的兴趣也在增加。 Landsat-8的热红外传感器(TIRS)是Landsat数据连续性任务(LDCM)的最新TIR传感器,具有两个相邻的红外热波段(10、11),对地表温度反演具有重要的好处。可以通过Landsat-8 OLI_TIRS卫星图像的TIR波段10和11估算光谱辐射度。在本研究中,已采用基于辐射传递方程的方法估算拉合尔的LST,分析表明,从辐射传递方法到频带10,估算的LST具有最高的准确度。借助NDVI的阈值技术。本研究结果表明,随着建筑面积的增加和城市地表植被的减少,它们与城市地表温度的升高有关,反之则与较低的城市温度相关的植被地表更大。产出暴露出,LST在人满为患和贫瘠的土地上较高,而在有更多植被和水的地区则较低。

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