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  • ACRS 1999


    Global Change
    Energy Distribution of Land Surface in China Based on Remote Sensing and GIS

    Distribution of cold and heat sources in China
    If energy from solar radiation and energy exchange between land surface and atmosphere was greater than the energy surrounding area the heat was transferred into the surrounding area through soil heat flux, sensible heat flux and latent heat flux. On the contrary, the heat in surrounding area would be transferred into this area. This area is called as heat or cold source.

    Temporal and spatial change of cold and heat sources relates the discrepancy of heat actions of land surface directly. Their distribution is very important to atmospheric movement, atmospheric circulation form and change. The cold and heat sources can be calculated through amount calculation of energy balance. The distribution of cold and heat sources can be obtained when the net radiation and soil heat flux or sensible and latent heat fluxes are known. The equation of energy balance is

    Rn = LE + H + G

    Where Rn: net radiation; LE: latent heat flux; H: sensible heat flux and G: soil heat flux.
    When
    Rn – G = LE + H > 0,             as heat source

    Rn – G = LE + H < 0,             as cold source

    The monthly distribution of cold and heat sources was derived. The cold source distributed in January and February, November and December and the distributions in other months were heat source. The distribution of cold area in January and December spreaded in large area from the distribution map of cold source. The area in February and November taken second place that mainly distributed in Northeastern, Northern of Xingjiang and Qingzang plateau. The cold area located in the region where yearly mean air temperature was less than 0°C and in the region of high albedo.

    Conclusions
    • The data bases of land cover type in China was built and energy balance of land surface was calculated using remote sensing and GIS so that made reasonable coupling between energy transformation process and land cover type.
    • The data base of climate planning in China was introduced into the energy balance model so that the energy distribution could more reflect regional feature of climate. The results of radiation calculation more indicated the regional effect.
    • the model of actual evapotranspiration of land surface in China has been developed based on land cover type and land surface feature model. The results indicated that evapotranspiration distribution of land surface in China in summer was greater than that in winter. The ET in high latitude area was less than that in low latitude area, and ET in east part of China was greater than the ET in west part. Climate property, land cover type, precipitation distribution and human being activity are the main factors that influenced regional ET.
    • Monthly distribution of cold and heat sources has been calculated. The heat source distributed from March to October in 1997. There were large areas of cold source in November-December and January-February in Northeast, North part of Xingjiang, Qingzang Plateau. The yearly mean temperature was lower than zero degree in these cold areas, the land surface was covered by snow and yearly mean albedo was much more higher in the regions.
    • It is necessary to establish data base of priori knowledge for computation of LSE, and also feasible. It provides a useful mean for study on Energy balance of land surface in regions.
    • It is very important for improving accuracy of LSE calculation using combination of GIS with conventional methods and their comprehensive applications.
    Reference
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    • Brest, C. L. And Samuel n. Groward, 1987, Deriving surface albedo measurement from narrow band satellite data, INT. Re. Sens., Vol. 8, No. 3.
    • Brown, K. W. and N. J. Rosenber, 1973, A resistance model to predict evapotanspiration and its applications to a sugar beet field, Argon. J., 65.
    • Dickinson, R. E., et al, 1986, Biosphere-atmosphere transfer scheme (BATS) for the NCAR community climate model, Atmosphere Analysis and Prediction Division, National Center for Atmosphere Research Boulder, Colorado.
    • Javis P. G., 1976, the interpretation of the variation in leaf water potential and stomatal conductance found in canopies in the field, Phi. Trans. R. Soc. Lond. B, 273.
    • Li, Z. L., 1993, Feasibility of land surface temperature and emissivity determination from AVHRR data, Remote Sensing Environ., 43.
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    • Qin Yi and Tian Guoliang, 1994, A research on the method and computer program of correction of atmosphere effects on NOAA-AVHRR image, part one: principle and model, Remote Sensing of Environ. in China, Vol. 9, No. 1.
    • Sobrino, J. A., 1994, Improvements in the split-window technique for land surface temperature determination, IEEE Trans. On Geoscience and Remote Sensing, Vol. 32, No. 12.
    • Thom, A. S., 1975, Momentum, mass and heat exchange of plant communities, In J. L. Monteith, Vegetation and the atmosphere, Vol. 1, Principle, Academic Press, London.
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    • Walthall, C. L., et al, 1985, Simple equation to approximate the bidirectional reflectance from vegetation canopies and bare soil surface, Appl. Opt., Vol. 24, No. 3.
    • Wolfgang, W. et al, 1995, On the derivation of kernels for kernel-driven models of bidirectional reflectance, J. Geographical Research.
    • Xu, X. K., et al, 1999, Application of complementary relationship model for satellite remote sensing, Chinese J. Remote Sensing, Vol. 3, No. 1.
    • Xu, X. K., 1999, Analysis of land surface energy characteristics in China based on remote sensing and GIS, PHD thesis, Institute of Remote Sensing Applications, Chinese Academy of Sciences.
    • Zhou Xiuji, 1995, Atmosphere prediction, dynamic GIS and Remote Sensing, Annual Report, LARSIS, IRSA, CAS.
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