Google Earth Engine Open-Source Code for Land Surface Temperature Estimation from the Landsat Series

被引:412
作者
Ermida, Sofia L. [1 ,2 ]
Soares, Patricia [3 ]
Mantas, Vasco [3 ]
Goettsche, Frank-M [4 ]
Trigo, Isabel E. [1 ,2 ]
机构
[1] Inst Portugues Mar & Atmosfera IPMA, P-1749077 Lisbon, Portugal
[2] Univ Lisbon, Fac Ciencias, Inst Dom Luiz IDL, P-1749016 Lisbon, Portugal
[3] Univ Coimbra, Dept Earth Sci, P-3030790 Coimbra, Portugal
[4] Karlsruhe Inst Technol KIT, Inst Meteorol & Climate Res IMK ASF, D-76021 Karlsruhe, Germany
关键词
Land Surface Temperature; Landsat; Google Earth Engine; ASTER GED; high resolution; FRACTIONAL VEGETATION COVER; MONO-WINDOW ALGORITHM; SPATIAL-PATTERN; RETRIEVAL; VALIDATION; TM; PRODUCTS; EVAPOTRANSPIRATION; GENERATION; LANDSCAPE;
D O I
10.3390/rs12091471
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Land Surface Temperature (LST) is increasingly important for various studies assessing land surface conditions, e.g., studies of urban climate, evapotranspiration, and vegetation stress. The Landsat series of satellites have the potential to provide LST estimates at a high spatial resolution, which is particularly appropriate for local or small-scale studies. Numerous studies have proposed LST retrieval algorithms for the Landsat series, and some datasets are available online. However, those datasets generally require the users to be able to handle large volumes of data. Google Earth Engine (GEE) is an online platform created to allow remote sensing users to easily perform big data analyses without increasing the demand for local computing resources. However, high spatial resolution LST datasets are currently not available in GEE. Here we provide a code repository that allows computing LSTs from Landsat 4, 5, 7, and 8 within GEE. The code may be used freely by users for computing Landsat LST as part of any analysis within GEE.
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页数:21
相关论文
共 75 条
[41]   Quality Assessment of S-NPP VIIRS Land Surface Temperature Product [J].
Liu, Yuling ;
Yu, Yunyue ;
Yu, Peng ;
Goettsche, Frank M. ;
Trigo, Isabel F. .
REMOTE SENSING, 2015, 7 (09) :12215-12241
[42]   Effects of green space spatial pattern on land surface temperature: Implications for sustainable urban planning and climate change adaptation [J].
Maimaitiyiming, Matthew ;
Ghulam, Abduwasit ;
Tiyip, Tashpolat ;
Pla, Filiberto ;
Latorre-Carmona, Pedro ;
Halik, Uemuet ;
Sawut, Mamat ;
Caetano, Mario .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2014, 89 :59-66
[43]   Comprehensive In Situ Validation of Five Satellite Land Surface Temperature Data Sets over Multiple Stations and Years [J].
Martin, Maria Anna ;
Ghent, Darren ;
Pires, Ana Cordeiro ;
Goettsche, Frank-Michael ;
Cermak, Jan ;
Remedios, John J. .
REMOTE SENSING, 2019, 11 (05)
[44]  
Martins J.P., 2019, COPERNICUS GLOBAL LA
[45]   A Physically Constrained Calibration Database for Land Surface Temperature Using Infrared Retrieval Algorithms [J].
Martins, Joao P. A. ;
Trigo, Isabel F. ;
Bento, Virigilio A. ;
da Camara, Carlos .
REMOTE SENSING, 2016, 8 (10)
[46]   Estimating Land Surface Temperature from Landsat-8 Data using the NOAA JPSS Enterprise Algorithm [J].
Meng, Xiangchen ;
Cheng, Jie ;
Zhao, Shaohua ;
Liu, Sihan ;
Yao, Yunjun .
REMOTE SENSING, 2019, 11 (02)
[47]   Calculating potential evapotranspiration and single crop coefficient based on energy balance equation using Landsat 8 and Sentinel-2 [J].
Mokhtari, Ali ;
Noory, Hamideh ;
Pourshakouri, Farrokh ;
Haghighatmehr, Parisa ;
Afrasiabian, Yasamin ;
Razavi, Maryam ;
Fereydooni, Fatemeh ;
Naeni, Ali Sadeghi .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2019, 154 :231-245
[48]   Online Global Land Surface Temperature Estimation from Landsat [J].
Parastatidis, David ;
Mitraka, Zina ;
Chrysoulakis, Nektrarios ;
Abrams, Michael .
REMOTE SENSING, 2017, 9 (12)
[49]   Seasonal contrast of the dominant factors for spatial distribution of land surface temperature in urban areas [J].
Peng, Jian ;
Jia, Jinglei ;
Liu, Yanxu ;
Li, Huilei ;
Wu, Jiansheng .
REMOTE SENSING OF ENVIRONMENT, 2018, 215 :255-267
[50]   Emissivity maps to retrieve land-surface temperature from MSG/SEVIRI [J].
Peres, LF ;
DaCamara, CC .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2005, 43 (08) :1834-1844