Using Satellite Remotely Sensed Data to Retrieve Sensible and Latent Heat Fluxes: A Review
Received date: 2003-08-13
Revised date: 2004-03-25
Online published: 2005-01-25
Regional sensible and latent heat fluxes are the key physical parameters of the meteorological, hydrological and ecological models. However it is very difficult to obtain these fluxes from conventional ground measurement. Using satellite remotely sensed data to retrieve these fluxes supplies one possible way to solve this problem. However, the gradient measurement is needed when calculating the fluxes are calculated, while the measurements from only one layer can be obtained from satellite. To solve this problem, many studies have been carried out. There are two main ways that can be seen: the physical model and empirical model. The physical models have two directions: the gradient model and the thermal inertia method. Gradient models combine the satellite remotely sensed data with the ground measurements, and use the difference of surface temperature and air temperature at reference height to calculate sensible heat flux. The latent heat flux is obtained as the residual. The thermal inertia method uses the response of soil to the absorption of solar radiation to calculate the sensible and latent heat flux. The empirical method calculates empirical regression between the measurements of the fluxes and the satellite remotely sensed data, and then extends this relationship to calculate the fluxes. Here the daily-average fluxes are often used.
Four gradient models are reviewed, including one one-source model and three two-source models. When use the onesource model is used for to partly vegetation-covered surface, the difference of the air dynamic temperature and the thermal radioactive temperature hinds it usage. Two-source models can solve this problem. However, all the gradient models are sensitive to the error of the difference between the satellite retrieved surface temperature and the measurements of the air temperature. Another shortcoming of the gradient model is that they need to interpolate ground measurements, such as the air temperature and wind speed. These interpolations always are of low quality with unacceptable errors. The thermal inertia method calculates sensible and latent heat fluxes only using the satellite remotely sensed data, which will have a wider usage in the near future. However, up to today, this method only succeeded in the bare soil surface. More attention should be paid to it in the future.
At last, the methods used to evaluate the accuracy of the retrieval of sensible and latent heat fluxes are reviewed.
Key words： Satellite remote sensing; Retrieve; Heat fluxes; Physical model; Accuracy evaluation
WANG Kaicun,Zhou Xiuji,LI Weiliang,LIU Jingmiao，WANG Pucai . Using Satellite Remotely Sensed Data to Retrieve Sensible and Latent Heat Fluxes: A Review[J]. Advances in Earth Science, 2005 , 20(1) : 42 -048 . DOI: 10.11867/j.issn.1001-8166.2005.01.0042
［1］Shuttleworth W J, Wallace J S. Evaporation from sparse crops-An energy combination theory[J].Quarterly Journal of the Royal Meteorological Society,1985,111:839-855.
［2］Zhang Lu, Lemeur R, Goutorbe J P. A one-layer resistance model for estimating regional evaportranspiration using remote sensing data[J].Agricultural and Forest Meteorology,1995,77: 241-261［3］Kustas W P, Choudhury B, Reginato,et al. Determination of sensible heat flux over sparse canopy using thermal infrared data[J].Agricultural and Forest Meteorology,1989,44:197-216.
［4］Ma Yaoming, Tsukamoto O, Ishikawa H, et al. Determination of regional land surface heat flux densities over heterogeneous landscape of HEIFE integrating satellite remote sensing with field observations [J].Journal of Meteorology Society of Japan, 2002,80: 485-501.
［5］Jacobsen A, Hansen B U. Estimation of the soil heat flux/ net radiation ratio based on spectral vegetation indexes in high-latitude Arctic areas [J].International Journal of Remote Sensing, 1999, 20(2): 445-461.
［6］Clothier B E, Clawson K L, Pinter, et al. Estimation of soil heat flux from net radiation during the growth of lfalfa [J].Agricultural and Forest Meteorology,1986, 37: 319- 329.
［7］Kustas W P, Daughtry C S T. Estimation of the soil heat flux-net radiation from spectral data[J].Agricultural and Forest Meteorology,1990, 49: 205-223.
［8］Kustas W P, Daughtry C S T, Van Oevelen P J. Analytical treatment of the relationships between soil heat flux/net radiation ratio and vegetation indices [J].Remote Sensing of Environment,1993, 46: 319-330.
［9］Monin A S, Oblukhov A M. Basic laws of turbulent mixing in the atmosphere near the ground[J].Trudy Geofizicheskogo Instituta Akademiya Nuak SSSR，1954, 24(151): 163-187.
［10］Businger J A, Wyngaard J C, Lzumi Y,et al. Flux profile relations in the atmospheric surface layer[J].Journal of Atmospheric Science,1971, 28: 181-189.
［11］Dyer A J. A review of the flux-profile relations [J].Boundary Layer Meteorology,1972,1: 336-372.
［12］Mecikalski John R, Diak George R, Anderson Martha C. Estimating fluxes on continental Scales using remotely sensing data in an atmospheric-land exchange model[J].Journal of Applied Meteorology,1999,38: 1 353-1 369.
［13］PauPach M R.Simplified expression for vegetation roughness length and zero-plane displacement as function of canopy height and area index[J].Boundary Layer Meteorology,1994,71: 211-216.
［14］Chehbouni A, LoSeen D, Njoku,et al. Examination of the difference between radiative and aerodynamic surface temperature over sparsely vegetated surfaces [J].Remote Sensing of Environment,1995, 58: 177-186.
［15］Friedl M A. Forward and inverse modeling of land surface energy balance using surface temperature measurements [J].Remote Sensing of Environment,2002,79: 344-354.
［16］Su Z, Schmugge T, Kusts W P. An evaluation of two models for estimation of the roughness height for heat transfer between the land surface and atmosphere[J].Journal of Applied Meteorology,2001,40(11): 1 933-1 951.
［17］Bl mel K. A simple formula for estimation of the roughness length for heat transfer over Partly vegetation surfaces [J].Journal of Applied Meteorology,1999, 38: 814-829.
［18］Verhoef W, de Bruin H A R, van den hurk B J M. Some practical notes on the parameter KB-1 for spares vegetation [J].Journal of Applied Meteorology,1997, 36: 560-572.
［19］Jia Li, Wang Jiemin, Hu Zeyong. The characteristics of roughness length for heat and it influence on the determination of sensible heat flux on arid zone[J].Plateau Meteorology,2000,19(4): 485-503.[贾立,王介民,胡泽勇.干旱区热力粗糙度特征及对感热通量估算的影响[J].高原气象，2000，19(4):485-503.]
［20］Norman J M, Kustas W P, Humes K S. Source approach for estimating soil and vegetation energy flux in observations of directional radiometric surface temperature [J].Agriculture and Forest Meteorology,1995,77: 263-293.
［21］Wallace J S. Evaporation, radiation interception by neighboring plants [J].Quarterly Journal of the Royal Meteorological Society,1997, 123:1 885-1 905.
［22］Lhomme J P, Chehbouni A. Comments on the vegetation-atmosphere transfer models [J].Agriculture and Forest Meteorology,1999, 94: 269-273.
［23］Kustas W P, Norman J M. Reply to comments on the basic equation of dual-source vegetation-atmosphere models [J].Agriculture and Forest Meteorology,1999, 94: 275-278.
［24］Kustas W P, Norman J M. Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover [J].Agriculture and Forest Meteorology,1999, 94: 13-29.
［25］Kondo J, Ishida S. Sensible heat flux from surface under natural convective conditions [J].Journal of Science,1997, 54: 498-509.
［26］Kustas W P, Prueger J H, Hipps L E. Impact of different time-averaged inputs for estimating sensible heat flux of riparian vegetation using radiometric surface temperature [J].Journal of Applied Meteorology,2002, 41: 319-332.
［27］Anderson M C, Norman J M, Dick G R,et al. A two-source time-integrated model for estimating surface flux using thermal infrared remote sensing [J].Remote Sensing of Environment,1997, 60: 195-216.
［28］Mercikalski J R, Dick G R, Anderson M C. Estimating flux on continental scales using remotely sensed data in an atmospheric-land exchange model [J].Journal of Applied Meteorology,1999, 38: 1 353-1 369.
［29］Norman J M, Kustas W P, Prueger J H. Surface flux estimation using radiometric temperature, a dual temperature difference method to minimize measurement errors [J].Water Resource Research,2000, 36(8): 2 263-2 274.
［30］Kustas W P, Goodrich D C, Moran M S,et al. An interdisciplinary field study of the energy and water fluxes in the atmosphere- biosphere system over semiarid rangeland, description and some preliminary results[J].Bulletin of America Meteorological Societiy,1991, 72: 1 683-1 705.
［31］Sellers P J, Asrar F G, Strebel G,et al. An overview of the first international satellite land surface climatology project (ISLSCP) field experiment (FIFE) [J].Journal of Geophysics Research,1992, 97(D17): 18 345-18 371.
［32］Zhang Renhua, Sun Xiaomin, Zhu Zhilin,et al. A remote sensing model for monitoring soil evaporation based on thermal inertia and its validation [J].Science in China (D),2003, 46(4): 342-355.［33］Ma Ainai. Remote Sensing Information Model [M].Beijing: Peking University Press, 1997. 41-51.[马蔼乃.遥感信息模型[M].北京：北京大学出版社，1997:41-51.]
［34］Price J C.Estimation of regional scale evapotranspiration through abbalist’s satellite thermal infrared data [J].IEEE Transaction on Geosciences and Remote Sensing,1982, 20: 286-292.
［35］Zhang Renhua. Inertia model of soil moisture and its application [J].Chinese Science Bulletin,1991, 36(12): 924-927.
［36］Goward Samuel N, Xue Yongkang, Czajkowski Kevin P. Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements: An exploration with the simplified simple biosphere model [J].Remote Sensing of Environment,2002, 79: 225-242.
［37］Rabin Robert M. Relating remotely sensed vegetation and soil indices to surface energy fluxes in vicinity of an atmosphere dryline [J].Remote Sensing Reviews,2000, 18: 53-58.
［38］Jiang L, Islam S. A methodology for estimation of surface evapotranspiration over large areas using remote sensing observations [J].Geophysical Research Letters,1999, 26(17): 2 773-2 776.
［39］Jiang L,Islam S.Estimation of surface evaporation map over southern Great Plains using remote sensing data [J].Water Resources Research,2001,37(2): 329-340
［40］Boegh E, Soegaard H, Hanan N,et al.A remote sensing study of the NDVI Ts relationship and the transpiration from sparse vegetation in the Sahel based on high resolution satellite data [J].Remote Sensing of Environment,1998, 69 (3): 224-240.
［41］Gillies R R, Carlson T N, Gui J,et al.A verification of the triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface radiant temperature [J].International Journal of Remote Sensing,1997,18 (15): 3 145-3 166.
［42］Sandholta Inge, Rasmussena Kjeld, Andersen Jens. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status [J].Remote Sensing of Environment,2002, 79: 213-224.
［43］Smith R C G, Choudhury B J. Analysis of normalized difference and surface temperature observations over southeastern Australia [J].International Journal of Remote Sensing,1991, 12 (10): 2 021-2 044.
［44］Bella C M DI, Rebella C M, Paruelo J M. Evapotranspiration estimates using NOAA AVHRR imagery in the Pampa region of Argentina [J].International Journal of Remote sensing,2000, 21(4): 791-797.
［45］Kustas W P, Norman J. Evaluating the effects of sub-pixel heterogeneity on pixel averaged fluxes [J].Remote Sensing of Environment,2000, 74(3): 327-343.
［46］Wang J, Ma Y, Menenti Mi,et al.The scaling-up process in the heterogeneous landscape of HEIFE with the aid of satellite remote sensing [J].Journal of Meteorology Society of Japan,1995, 73(6): 1 235-1 244.
［47］Liu Jingmiao, Ding Yuguo, Zhou Xiuji,et al.The influences of the surface heterogeneity on the parameterization of region averaged moisture flux [J].Acta Meteorologica Sinica,2003, 61(6): 712-717.[刘晶淼,丁裕国,周秀骥,等.地表非均匀性对区域平均水分通量参数化的影响[J].气象学报，2003, 61(6): 712-717.]
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