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1
Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature
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Conditioning a Hydrologic Model Using Patterns of Remotely Sensed Land Surface Temperature

Water resources research, 2018-04, Vol.54 (4), p.2976-2998 [Peer Reviewed Journal]

2018. American Geophysical Union. All Rights Reserved. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0043-1397 ;EISSN: 1944-7973 ;DOI: 10.1002/2017WR021346

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2
Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation
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Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation

Remote sensing (Basel, Switzerland), 2020-01, Vol.12 (2), p.294 [Peer Reviewed Journal]

2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12020294

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3
A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives
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A review of earth surface thermal radiation directionality observing and modeling: Historical development, current status and perspectives

Remote sensing of environment, 2019-10, Vol.232 [Peer Reviewed Journal]

Attribution ;ISSN: 0034-4257 ;EISSN: 1879-0704 ;DOI: 10.1016/j.rse.2019.111304

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4
Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy
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Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy

European journal of remote sensing, 2018-01, Vol.51 (1), p.667-678 [Peer Reviewed Journal]

2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2018 ;2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2279-7254 ;EISSN: 2279-7254 ;DOI: 10.1080/22797254.2018.1474494

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5
Aridity-Dependent Land Surface Skin Temperature Biases in CMIP5/6
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Aridity-Dependent Land Surface Skin Temperature Biases in CMIP5/6

Geophysical research letters, 2022-07, Vol.49 (15) [Peer Reviewed Journal]

ISSN: 0094-8276 ;EISSN: 1944-8007

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6
Summer drought weakens land surface cooling of tundra vegetation
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Summer drought weakens land surface cooling of tundra vegetation

ISSN: 1748-9326 ;EISSN: 1748-9326 ;DOI: 10.1088/1748-9326/ad345e

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7
Summer drought weakens land surface cooling of tundra vegetation
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Summer drought weakens land surface cooling of tundra vegetation

ISSN: 1748-9326 ;EISSN: 1748-9326 ;DOI: 10.1088/1748-9326/ad345e

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8
A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data
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A Practical Split-Window Algorithm for Estimating Land Surface Temperature from Landsat 8 Data

Remote sensing (Basel, Switzerland), 2015-01, Vol.7 (1), p.647-665 [Peer Reviewed Journal]

Copyright MDPI AG 2015 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs70100647

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9
Retrieval of Land Surface Temperature from Landsat-8 Thermal Infrared Sensor Data
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Retrieval of Land Surface Temperature from Landsat-8 Thermal Infrared Sensor Data

Journal of Human, Earth, and Future, 2022-06, Vol.3 (2), p.159-168 [Peer Reviewed Journal]

ISSN: 2785-2997 ;EISSN: 2785-2997 ;DOI: 10.28991/HEF-2022-03-02-02

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10
Marshland Loss Warms Local Land Surface Temperature in China
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Marshland Loss Warms Local Land Surface Temperature in China

Geophysical research letters, 2020-03, Vol.47 (6), p.n/a [Peer Reviewed Journal]

2020. The Authors. ;2020. American Geophysical Union. All Rights Reserved. ;ISSN: 0094-8276 ;EISSN: 1944-8007 ;DOI: 10.1029/2020GL087648

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11
An assessment on the relationship between land surface temperature and normalized difference vegetation index
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An assessment on the relationship between land surface temperature and normalized difference vegetation index

Environment, development and sustainability, 2021-02, Vol.23 (2), p.1944-1963 [Peer Reviewed Journal]

Springer Nature B.V. 2020 ;Springer Nature B.V. 2020. ;ISSN: 1387-585X ;EISSN: 1573-2975 ;DOI: 10.1007/s10668-020-00657-6

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12
Estimation of land surface temperature over the Tibetan Plateau based on Sentinel-3 SLSTR data
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Estimation of land surface temperature over the Tibetan Plateau based on Sentinel-3 SLSTR data

IEEE journal of selected topics in applied earth observations and remote sensing, 2023-01, Vol.16, p.1-15 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 ;ISSN: 1939-1404 ;EISSN: 2151-1535 ;DOI: 10.1109/JSTARS.2023.3268326 ;CODEN: IJSTHZ

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13
An Analyze of Urban Temperature Using Energy Balance Algorithm for Land (SEBAL) in Yogyakarta City
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An Analyze of Urban Temperature Using Energy Balance Algorithm for Land (SEBAL) in Yogyakarta City

Jurnal tanah Tropika dan Kualitas Lingkungan, 2022-09, Vol.28 (1), p.31-38

ISSN: 0852-257X ;EISSN: 2086-6682 ;DOI: 10.5400/jts.2023.v28i1.31-38

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14
Study of land cover/land use changes using RS and GIS: a case study of Multan district, Pakistan
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Article
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Study of land cover/land use changes using RS and GIS: a case study of Multan district, Pakistan

Environmental monitoring and assessment, 2020-01, Vol.192 (1), p.2-2, Article 2 [Peer Reviewed Journal]

Springer Nature Switzerland AG 2019 ;Environmental Monitoring and Assessment is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0167-6369 ;EISSN: 1573-2959 ;DOI: 10.1007/s10661-019-7959-1 ;PMID: 31792634

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15
Spatio-temporal dynamic land cover changes and their impacts on the urban thermal environment in the Chittagong metropolitan area, Bangladesh
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Article
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Spatio-temporal dynamic land cover changes and their impacts on the urban thermal environment in the Chittagong metropolitan area, Bangladesh

GeoJournal, 2021-10, Vol.86 (5), p.2119-2134 [Peer Reviewed Journal]

Springer Nature B.V. 2020 ;Springer Nature B.V. 2020. ;ISSN: 0343-2521 ;EISSN: 1572-9893 ;DOI: 10.1007/s10708-020-10178-4

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16
Predicting Land Surface Temperature and Land Cover Changes Based on Multi-Source Remote Sensing Spatio-Temporal Fusion in Hefei, Eastern China
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Predicting Land Surface Temperature and Land Cover Changes Based on Multi-Source Remote Sensing Spatio-Temporal Fusion in Hefei, Eastern China

IEEE journal of selected topics in applied earth observations and remote sensing, 2023-08, p.1-18 [Peer Reviewed Journal]

ISSN: 1939-1404 ;EISSN: 2151-1535 ;DOI: 10.1109/JSTARS.2023.3306275 ;CODEN: IJSTHZ

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17
Evaluating global and regional land warming trends in the past decades with both MODIS and ERA5-Land land surface temperature data
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Article
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Evaluating global and regional land warming trends in the past decades with both MODIS and ERA5-Land land surface temperature data

Remote sensing of environment, 2022-10 [Peer Reviewed Journal]

info:eu-repo/semantics/openAccess ;ISSN: 0034-4257 ;EISSN: 1879-0704 ;DOI: 10.1016/j.rse.2022.113181

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18
Determination of global land surface temperature using data from only five selected thermal infrared channels: Method extension and accuracy assessment
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Article
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Determination of global land surface temperature using data from only five selected thermal infrared channels: Method extension and accuracy assessment

Remote sensing of environment, 2022-01, Vol.268 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0034-4257 ;EISSN: 1879-0704 ;DOI: 10.1016/j.rse.2021.112774

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19
Mapping Paddy Rice Using a Convolutional Neural Network (CNN) with Landsat 8 Datasets in the Dongting Lake Area, China
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Mapping Paddy Rice Using a Convolutional Neural Network (CNN) with Landsat 8 Datasets in the Dongting Lake Area, China

Remote sensing (Basel, Switzerland), 2018-11, Vol.10 (11), p.1840 [Peer Reviewed Journal]

2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs10111840

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20
Multi-scale impacts of 2D/3D urban building pattern in intra-annual thermal environment of Hangzhou, China
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Multi-scale impacts of 2D/3D urban building pattern in intra-annual thermal environment of Hangzhou, China

International journal of applied earth observation and geoinformation, 2021-12, Vol.104, p.102558, Article 102558 [Peer Reviewed Journal]

2021 The Authors ;ISSN: 1569-8432 ;EISSN: 1872-826X ;DOI: 10.1016/j.jag.2021.102558

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