Heat Flux

Chapter Contents (Back)
Heat Flux.
See also Land Surface Temperature, Remote Sensing.
See also Solar Radiation, Solar Irradiance, Measurements. Some overlap:
See also Atmospheric Boundary Layer Height.
See also Upward Longwave Radiation, Outgoing Longwave Radiation, Upwelling Radiation.

Zahira, S., Abderrahmane, H., Mederbal, K., Frederic, D.,
Mapping Latent Heat Flux in the Western Forest Covered Regions of Algeria Using Remote Sensing Data and a Spatialized Model,
RS(1), No. 4, December 2009, pp. 795-817.
DOI Link 1203

Maltese, A.[Antonino], Awada, H.[Hassan], Capodici, F.[Fulvio], Ciraolo, G.[Giuseppe], Loggia, G.L.[Goffredo La], Rallo, G.[Giovanni],
On the Use of the Eddy Covariance Latent Heat Flux and Sap Flow Transpiration for the Validation of a Surface Energy Balance Model,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804

Sun, Y.[Yibo], Jia, L.[Li], Chen, Q.T.[Qi-Ting], Zheng, C.L.[Chao-Lei],
Optimizing Window Length for Turbulent Heat Flux Calculations from Airborne Eddy Covariance Measurements under Near Neutral to Unstable Atmospheric Stability Conditions,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806

Kumar, S.[Sujay], Holmes, T.[Thomas], Mocko, D.M.[David M.], Wang, S.[Shugong], Peters-Lidard, C.[Christa],
Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
Plant and soil loss. BibRef

Dhungel, R.[Ramesh], Allen, R.G.[Richard G.], Trezza, R.[Ricardo], Robison, C.W.[Clarence W.],
Comparison of Latent Heat Flux Using Aerodynamic Methods and Using the Penman-Monteith Method with Satellite-Based Surface Energy Balance,
RS(6), No. 9, 2014, pp. 8844-8877.
DOI Link 1410

Feng, F.[Fei], Chen, J.Q.[Ji-Quan], Li, X.L.[Xiang-Lan], Yao, Y.J.[Yun-Jun], Liang, S.L.[Shun-Lin], Liu, M.[Meng], Zhang, N.N.[Nan-Nan], Guo, Y.[Yang], Yu, J.[Jian], Sun, M.[Minmin],
Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems,
RS(7), No. 12, 2015, pp. 15853.
DOI Link 1601

Yang, Y.M.[Yong-Min], Qiu, J.X.[Jian-Xiu], Su, H.B.[Hong-Bo], Bai, Q.M.[Qing-Mei], Liu, S.[Suhua], Li, L.[Lu], Yu, Y.L.[Yi-Lei], Huang, Y.X.[Yao-Xian],
A One-Source Approach for Estimating Land Surface Heat Fluxes Using Remotely Sensed Land Surface Temperature,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702

Eswar, R.[Rajasekaran], Sekhar, M.[Muddu], Bhattacharya, B.K.[Bimal K.], Bandyopadhyay, S.[Soumya],
Spatial Disaggregation of Latent Heat Flux Using Contextual Models over India,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711

Liu, K.[Kai], Su, H.B.[Hong-Bo], Li, X.[Xueke],
Comparative Assessment of Two Vegetation Fractional Cover Estimating Methods and Their Impacts on Modeling Urban Latent Heat Flux Using Landsat Imagery,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706

Chen, S.S.[Shan-Shan], Hu, D.[Deyong],
Parameterizing Anthropogenic Heat Flux with an Energy-Consumption Inventory and Multi-Source Remote Sensing Data,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712

He, X.L.[Xin-Lei], Xu, T.R.[Tong-Ren], Bateni, S.M.[Sayed M.], Neale, C.M.U.[Christopher M. U.], Auligne, T.[Thomas], Liu, S.M.[Shao-Min], Wang, K.C.[Kai-Cun], Mao, K.B.[Ke-Biao], Yao, Y.J.[Yun-Jun],
Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901

Wang, S.S.[Sha-Sha], Hu, D.Y.[De-Yong], Chen, S.S.[Shan-Shan], Yu, C.[Chen],
A Partition Modeling for Anthropogenic Heat Flux Mapping in China,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905

Wang, Y.[Yipu], Li, R.[Rui], Min, Q.L.[Qi-Long], Zhang, L.[Leiming], Yu, G.R.[Gui-Rui], Bergeron, Y.[Yves],
Estimation of Vegetation Latent Heat Flux over Three Forest Sites in ChinaFLUX using Satellite Microwave Vegetation Water Content Index,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906

Krayenhoff, E.S.[E. Scott], Wu, Z.F.[Zhi-Feng], Shi, Q.[Qian], Ouyang, X.Y.[Xiao-Ying],
Parameterization of Urban Sensible Heat Flux from Remotely Sensed Surface Temperature: Effects of Surface Structure,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906

Cheng, Z.[Zian], Pang, X.P.[Xiao-Ping], Zhao, X.[Xi], Stein, A.[Alfred],
Heat Flux Sources Analysis to the Ross Ice Shelf Polynya Ice Production Time Series and the Impact of Wind Forcing,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902

Crespo, J.A.[Juan A.], Posselt, D.J.[Derek J.], Asharaf, S.[Shakeel],
CYGNSS Surface Heat Flux Product Development,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910

Ge, N.[Nan], Zhong, L.[Lei], Ma, Y.M.[Yao-Ming], Cheng, M.L.[Mei-Lin], Wang, X.[Xian], Zou, M.J.[Mi-Jun], Huang, Z.Y.[Zi-Yu],
Estimation of Land Surface Heat Fluxes Based on Landsat 7 ETM+ Data and Field Measurements over the Northern Tibetan Plateau,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912

Li, X.J.[Xiao-Jun], Xin, X.Z.[Xiao-Zhou], Jiao, J.J.[Jing-Jun], Peng, Z.Q.[Zhi-Qing], Zhang, H.L.[Hai-Long], Shao, S.S.[Shan-Shan], Liu, Q.H.[Qin-Huo],
Estimating Subpixel Surface Heat Fluxes through Applying Temperature-Sharpening Methods to MODIS Data,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708

Wang, X.Y.[Xuan-Yu], Yao, Y.J.[Yun-Jun], Zhao, S.H.[Shao-Hua], Jia, K.[Kun], Zhang, X.T.[Xiao-Tong], Zhang, Y.[Yuhu], Zhang, L.[Lilin], Xu, J.[Jia], Chen, X.W.[Xiao-Wei],
MODIS-Based Estimation of Terrestrial Latent Heat Flux over North America Using Three Machine Learning Algorithms,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802

Yang, C.[Cheng], Wu, T.[Tonghua], Wang, J.[Jiemin], Yao, J.[Jimin], Li, R.[Ren], Zhao, L.[Lin], Xie, C.[Changwei], Zhu, X.F.[Xiao-Fan], Ni, J.[Jie], Hao, J.[Junming],
Estimating Surface Soil Heat Flux in Permafrost Regions Using Remote Sensing-Based Models on the Northern Qinghai-Tibetan Plateau under Clear-Sky Conditions,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903

Nkwinkwa Njouodo, A.S.I.[Arielle Stela Imbol], Rouault, M.[Mathieu], Johannessen, J.A.[Johnny A.],
Latent Heat Flux in the Agulhas Current,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907

Shang, K.[Ke], Yao, Y.J.[Yun-Jun], Li, Y.[Yufu], Yang, J.M.[Jun-Ming], Jia, K.[Kun], Zhang, X.T.[Xiao-Tong], Chen, X.W.[Xiao-Wei], Bei, X.Y.[Xiang-Yi], Guo, X.Z.[Xiao-Zheng],
Fusion of Five Satellite-Derived Products Using Extremely Randomized Trees to Estimate Terrestrial Latent Heat Flux over Europe,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003

Hossain, K.[Kabir], Villebro, F.[Frederik], Forchhammer, S.[Søren],
UAV image analysis for leakage detection in district heating systems using machine learning,
PRL(140), 2020, pp. 158-164.
Elsevier DOI 2012
CNN, SVM, RF, Adaboost, Energy leakage detection, District heating systems BibRef

Acharya, B.[Bibek], Sharma, V.[Vivek], Heitholt, J.[James], Tekiela, D.[Daniel], Nippgen, F.[Fabian],
Quantification and Mapping of Satellite Driven Surface Energy Balance Fluxes in Semi-Arid to Arid Inter-Mountain Region,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012

Acharya, B.[Bibek], Sharma, V.[Vivek],
Comparison of Satellite Driven Surface Energy Balance Models in Estimating Crop Evapotranspiration in Semi-Arid to Arid Inter-Mountain Region,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105

Cristóbal, J.[Jordi], Prakash, A.[Anupma], Anderson, M.C.[Martha C.], Kustas, W.P.[William P.], Alfieri, J.G.[Joseph G.], Gens, R.[Rudiger],
Surface Energy Flux Estimation in Two Boreal Settings in Alaska Using a Thermal-Based Remote Sensing Model,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012

Kim, J.[Jaemin], Lee, Y.G.[Yun Gon],
Characteristics of Satellite-Based Ocean Turbulent Heat Flux around the Korean Peninsula and Relationship with Changes in Typhoon Intensity,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101

Wang, L.[Lu], Zhang, Y.[Yuhu], Yao, Y.[Yunjun], Xiao, Z.Q.[Zhi-Qiang], Shang, K.[Ke], Guo, X.Z.[Xiao-Zheng], Yang, J.M.[Jun-Ming], Xue, S.H.[Shu-Hui], Wang, J.[Jie],
GBRT-Based Estimation of Terrestrial Latent Heat Flux in the Haihe River Basin from Satellite and Reanalysis Datasets,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104

Simpson, J.E.[Jake E.], Holman, F.[Fenner], Nieto, H.[Hector], Voelksch, I.[Ingo], Mauder, M.[Matthias], Klatt, J.[Janina], Fiener, P.[Peter], Kaplan, J.O.[Jed O.],
High Spatial and Temporal Resolution Energy Flux Mapping of Different Land Covers Using an Off-the-Shelf Unmanned Aerial System,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104

de Andrade, B.C.C.[Bruno César Comini], Pedrollo, O.C.[Olavo Correa], Ruhoff, A.[Anderson], Moreira, A.A.[Adriana Aparecida], Laipelt, L.[Leonardo], Kayser, R.B.[Rafael Bloedow], Biudes, M.S.[Marcelo Sacardi], Costa dos Santos, C.A.[Carlos Antonio], Roberti, D.R.[Debora Regina], Machado, N.G.[Nadja Gomes], Dalmagro, H.J.[Higo Jose], Antonino, A.C.D.[Antonio Celso Dantas], de Sousa Lima, J.R.[José Romualdo], de Souza, E.S.[Eduardo Soares], Souza, R.[Rodolfo],
Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link 2106

Zhang, L.L.[Li-Lin], Yao, Y.J.[Yun-Jun], Bei, X.Y.[Xiang-Yi], Li, Y.[Yufu], Shang, K.[Ke], Yang, J.M.[Jun-Ming], Guo, X.Z.[Xiao-Zheng], Yu, R.Y.[Rui-Yang], Xie, Z.J.[Zi-Jing],
ERTFM: An Effective Model to Fuse Chinese GF-1 and MODIS Reflectance Data for Terrestrial Latent Heat Flux Estimation,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109

Akkermans, T.[Tom], Clerbaux, N.[Nicolas],
Retrieval of Daily Mean Top-of-Atmosphere Reflected Solar Flux Using the Advanced Very High Resolution Radiometer (AVHRR) Instruments,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109

Taylor, H.[Heather], Vreugdenburg, M.[Melissa], Sangalli, L., Vincent, R.[Ron],
RMCSat: An F10.7 Solar Flux Index CubeSat Mission,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112

Khan, M.S.[Muhammad Sarfraz], Jeon, S.B.[Seung Bae], Jeong, M.H.[Myeong-Hun],
Gap-Filling Eddy Covariance Latent Heat Flux: Inter-Comparison of Four Machine Learning Model Predictions and Uncertainties in Forest Ecosystem,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112

Peng, Z.[Zhong], Tang, R.[Ronglin], Jiang, Y.[Yazhen], Liu, M.[Meng], Li, Z.L.[Zhao-Liang],
Global estimates of 500m daily aerodynamic roughness length from MODIS data,
PandRS(183), 2022, pp. 336-351.
Elsevier DOI 2201
Land surface turbulent heat fluxes . Aerodynamic roughness length, Machine learning, MODIS, Evapotranspiration BibRef

Bonsoms, J.[Josep], Boulet, G.[Gilles],
Ensemble Machine Learning Outperforms Empirical Equations for the Ground Heat Flux Estimation with Remote Sensing Data,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205

Chickadel, C.C.[C. Chris], Branch, R.[Ruth], Asher, W.E.[William E.], Jessup, A.T.[Andrew T.],
Laboratory Heat Flux Estimates of Seawater Foam for Low Wind Speeds,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205

Zhang, B.[Biao], Yu, X.T.[Xiao-Tong], Perrie, W.[William], Zhou, F.[Fenghua],
Air-Sea Interface Parameters and Heat Flux from Neural Network and Advanced Microwave Scanning Radiometer Observations,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206

Yao, Y.J.[Yun-Jun], Zhang, X.T.[Xiao-Tong], Levy, G.[Gad], Jia, K.[Kun], Al-Quraishi, A.M.F.[Ayad M. Fadhil],
Advances in Land-Ocean Heat Fluxes Using Remote Sensing,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208

Li, H.Y.[Hong-Yi], Zhou, L.[Libo], Wang, G.[Ge],
The Observed Impact of the South Asian Summer Monsoon on Land-Atmosphere Heat Transfers and Its Inhomogeneity over the Tibetan Plateau,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208

Tian, Y.Z.[Ying-Ze], Xu, T.R.[Tong-Ren], Chen, F.[Fei], He, X.L.[Xin-Lei], Li, S.[Shi],
Can Data Assimilation Improve Short-Term Prediction of Land Surface Variables?,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211

Kim, M.S.[Min-Seong], Kwon, B.H.[Byung Hyuk], Goo, T.Y.[Tae-Young], Jung, S.P.[Sueng-Pil],
Dropsonde-Based Heat Fluxes and Mixed Layer Height over the Sea Surface near the Korean Peninsula,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301

Wang, S.Z.[Shu-Zhou], Ma, Y.M.[Yao-Ming], Liu, Y.X.[Yu-Xin],
Simulated Trends in Land Surface Sensible Heat Flux on the Tibetan Plateau in Recent Decades,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302

Njuki, S.M.[Sammy M.], Mannaerts, C.M.[Chris M.], Su, Z.[Zhongbo],
Accounting for Turbulence-Induced Canopy Heat Transfer in the Simulation of Sensible Heat Flux in SEBS Model,
RS(15), No. 6, 2023, pp. 1578.
DOI Link 2304

Lin, J.[Jing], Xu, T.R.[Tong-Ren], Zhang, G.Q.[Gang-Qiang], He, X.P.[Xiang-Ping], Liu, S.M.[Shao-Min], Xu, Z.[Ziwei], Zhao, L.F.[Li-Fang], Xu, Z.[Zongbin], Wang, J.C.[Jian-Cheng],
Upscaling of Latent Heat Flux in Heihe River Basin Based on Transfer Learning Model,
RS(15), No. 7, 2023, pp. 1901.
DOI Link 2304

Lin, J.S.[Jin-Song], Wang, Y.F.[Yan-Feng], Pan, H.D.[Hai-Dong], Wei, Z.[Zexun], Xu, T.F.[Teng-Fei],
Uncertainty of CYGNSS-Derived Heat Flux Variations at Diurnal to Seasonal Time Scales over the Tropical Oceans,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307

Benkovitz, A.[Ayelet], Zafrir, H.[Hovav], Reuveni, Y.[Yuval],
A Novel Assessment of the Surface Heat Flux Role in Radon (Rn-222) Gas Flow within Subsurface Geological Porous Media,
RS(15), No. 16, 2023, pp. 4094.
DOI Link 2309

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Upward Longwave Radiation, Outgoing Longwave Radiation, Upwelling Radiation .

Last update:Aug 31, 2023 at 09:37:21