scholarly journals Estimation of land surface Temperature of Maiduguri Metropolitan Area: A Case Study of Jere & some part of Mafa using Landsat 8 Operational Land Image (OLI)

2020 ◽  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Metropolitan Area ◽  
Land Surface ◽  
Landsat 8

scholarly journals An estimation of the accuracy of the topoclimate range based on the land surface temperature with reference to a case study of the Drawa National Park, Poland

2020 ◽  
Vol 142 (1-2) ◽  
pp. 369-379
Author(s):  
Marek Półrolniczak ◽  
Aleksandra Zwolska ◽  
Leszek Kolendowicz
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
National Park ◽  
Thermal Conditions ◽  
Landsat 8 ◽  
Digital Maps ◽  
Almost All ◽  
Terra Satellite

Abstract Topoclimate depends on specifically local-scale climatic features caused by the interrelations between topography, water, soil, and land cover. The main purpose of this study is to identify, characterize, and delimit the range of topoclimate types at the Drawa National Park (DPN) and to estimate their accuracy while taking into consideration the thermal conditions of the land surface. Based on a set of digital maps, and with the use of the heat-balance Paszyński method, seven types of topoclimate were distinguished. Next, with the use of Landsat 8 and Terra satellite images, the DPN’s land surface temperature (LST) was calculated. The estimation of LST using the distinguished types of topoclimate allowed for determining their degree of quantity diversification as well as assessing the differences between those types. The obtained LST values indicated statistically significant differences between the medians of LST values for almost all of the distinguished topoclimate types, thereby confirming the suitability of the applied topoclimate determination procedure.

scholarly journals Effect of land cover composition and building configuration on land surface temperature in an urban-sprawl city, case study in Bangkok Metropolitan Area, Thailand

Heliyon ◽  
2020 ◽  
Vol 6 (8) ◽  
pp. e04485
Author(s):  
Tratrin Adulkongkaew ◽  
Tunlawit Satapanajaru ◽  
Sujittra Charoenhirunyingyos ◽  
Wichitra Singhirunnusorn
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Metropolitan Area ◽  
Urban Sprawl ◽  
Land Surface

Impact of urban greenspace spatial pattern on land surface temperature: a case study in Beijing metropolitan area, China

2019 ◽  
Vol 34 (12) ◽  
pp. 2949-2961 ◽  
Author(s):  
Jie Yin ◽  
Xiaoxu Wu ◽  
Miaogen Shen ◽  
Xiaoli Zhang ◽  
Chenghao Zhu ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Spatial Pattern ◽  
Land Surface Temperature ◽  
Metropolitan Area ◽  
Land Surface ◽  
Urban Greenspace ◽  
Beijing Metropolitan Area

scholarly journals A Comparative Analysis of Retrieval Algorithms of Land Surface Temperature from Landsat-8 Data: A Case Study of Shanghai, China

2021 ◽  
Vol 18 (11) ◽  
pp. 5659
Author(s):  
Yue Jiang ◽  
WenPeng Lin
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Single Channel ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Thermal Infrared Remote Sensing ◽  
Retrieval Algorithms ◽  
Split Window Algorithm

In the trend of global warming and urbanization, frequent extreme weather has a severe impact on the lives of citizens. Land Surface Temperature (LST) is an essential climate variable and a vital parameter for land surface processes at local and global scales. Retrieving LST from global, regional, and city-scale thermal infrared remote sensing data has unparalleled advantages and is one of the most common methods used to study urban heat island effects. Different algorithms have been developed for retrieving LST using satellite imagery, such as the Radiative Transfer Equation (RTE), Mono-Window Algorithm (MWA), Split-Window Algorithm (SWA), and Single-Channel Algorithm (SCA). A case study was performed in Shanghai to evaluate these existing algorithms in the retrieval of LST from Landsat-8 images. To evaluate the estimated LST accurately, measured data from meteorological stations and the MOD11A2 product were used for validation. The results showed that the four algorithms could achieve good results in retrieving LST, and the LST retrieval results were generally consistent within a spatial scale. SWA is more suitable for retrieving LST in Shanghai during the summer, a season when the temperature and the humidity are both very high in Shanghai. Highest retrieval accuracy could be seen in cultivated land, vegetation, wetland, and water body. SWA was more sensitive to the error caused by land surface emissivity (LSE). In low temperature and a dry winter, RTE, SWA, and SCA are relatively more reliable. Both RTE and SCA were sensitive to the error caused by atmospheric water vapor content. These results can provide a reasonable reference for the selection of LST retrieval algorithms for different periods in Shanghai.

Analysis of the relationships between land surface temperature and spectral indices pre- and during pandemic using Landsat-8 images (case study: Gerbangkertosusila)

2021 ◽  
Author(s):  
Akmal Hafiudzan ◽  
Anggita Sulistyarini ◽  
Zahwa U. Hikmah ◽  
Rohanita S. Pratiwi ◽  
Levita Ardyagarini ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Landsat 8 ◽  
Spectral Indices

scholarly journals Land surface temperature retrieval for arid regions based on Landsat-8 TIRS data: a case study in Shihezi, Northwest China

2014 ◽  
Vol 6 (6) ◽  
pp. 704-716 ◽  
Author(s):  
Lei Yang ◽  
YunGang Cao ◽  
XiaoHua Zhu ◽  
ShengHe Zeng ◽  
GuoJiang Yang ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Arid Regions ◽  
Northwest China ◽  
Landsat 8 ◽  
Temperature Retrieval
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