收稿日期: 2010-03-16
修回日期: 2010-09-07
网络出版日期: 2010-11-10
基金资助
公益性行业(气象)科研专项“尺度水热通量观测系统的研制与应用研究”(编号:GYHY200706046);国家自然科学基金项目“地表水热通量卫星遥感的时间尺度扩展方法研究”(编号:40971204);国家重点基础研究发展计划项目“地表时空变化特征参数的遥感定量描述与尺度转换”(编号:2007CB714400)资助.
Method and Validation for Surface Fluxes Estimation based on Multi-scale Remotely Sensed Data
Received date: 2010-03-16
Revised date: 2010-09-07
Online published: 2010-11-10
地表水热通量(显热通量、潜热通量)的遥感估算在全球气候变化、水资源、生态环境等研究领域具有重要的应用价值。MODIS数据的空间分辨率较低(热红外波段星下点为1 km),而地球表面的几何物理属性又具有高度非均匀性,因而在实际应用中面临较严重的尺度问题。探讨了多源卫星数据(中高分辨率Landsat TM与中低分辨率MODIS)相结合估算像元通量的2种方法,分别利用高分辨率的地表分类及植被指数信息在混合像元内部进行亚像元处理,以提高非均匀地表混合像元的通量估算精度。研究数据来自于2008年黑河流域综合实验获取的遥感数据和辅助数据,验证数据来自于实验期间获取的不同下垫面的地表通量数据,包括涡度相关(EC)数据,以及大孔径闪烁仪(LAS)数据。计算结果表明,2种方法皆可在下垫面不均匀或者地表类型较复杂的情况下得到比较明显的纠正效果,纠正后的通量与观测更加接近。相比之下,利用植被指数分解温度的方法适用性更广,纠正效果更好。在地面验证中,对比分析了EC和 LAS数据在TM尺度和MODIS尺度通量验证的适用性。LAS数据测量尺度与MODIS卫星像元尺度相匹配,可以直接验证MODIS通量计算结果,EC数据虽然可以直接验证TM计算的通量,但与MODIS数据对比,还需要进行尺度转换,即先用EC验证TM通量,然后将TM通量降尺度,与MODIS进行对比。最后对利用LAS验证通量的不确定性进行了分析,发现图像中LAS测点的几何定位误差以及LAS测量路径中像元的选取都对验证结果有一定影响。
关键词: 遥感; 水热通量; 多尺度算法; 大孔径闪烁仪(LAS); 验证方法
刘雅妮,辛晓洲,柳钦火,周春艳 . 基于多尺度遥感数据估算地表通量的方法及其验证分析[J]. 地球科学进展, 2010 , 25(11) : 1261 -1272 . DOI: 10.11867/j.issn.1001-8166.2010.11.1261
Estimation of regional surface heat fluxes (sensible heat flux and latent heat flux) using remote sensing data is of important application value in the field of global climate change, water resource and ecological environment etc. The Moderate Resolution Imaging Spectroradiometer (MODIS) data has lower spatial resolution; however the geometric and physical properties of the Earth's surface also have a high degree of heterogeneity, which in practice are facing serious scaling problems. This paper discusses two methods of estimating the pixel fluxes using multi-source satellite data (the high-resolution Landsat TM data and low-resolution MODIS data), combining the land cover information or remotely sensed vegetation index provided by Landsat data with MODIS data to correct the spatial-scale errors. The remote sensing data and ancillary data used in this paper to evaluate the methods was obtained in comprehensive experiment held at Hei′he Watershed in 2008, validation data was surface flux data from the different surfaces during the experiment, including Eddy-Correlation (EC) data and Large Aperture Scintillometer (LAS) data. The results showed that, the combination method that use high resolution land class or vegetation index data can provide better estimation of surface heat fluxes, especially at the boundary of different land cover and heterogeneous land surfaces. By contrast, the method of using remotely sensed vegetation index provided by Landsat data to decompose temperature is more applicable and has a better validation result. The application of both Eddy-Correlation (EC) data and Large Aperture Scintillometer (LAS) data were analyzed by contrasting in the scaling process of fluxes validation by TM and MODIS. According to the pixel resolution of MODIS, LAS measurement can provided useful data at the scale of several kilometers, and can be used to validate MODIS fluxes directly. On the other hand, EC data need to be compared to the TM fluxes first, and then the downscaled TM fluxes can be used to validate MODIS fluxes. Finally, the uncertainties in the validation of fluxes using LAS data are mainly from the following aspect, ① the error from the positioning of the LAS site in the image; ② uncertainty in the contributing pixels of LAS observation in the image.
[1] Ma Yaoming,Wang Jiemin.A survey in the study of area evaporation (evapotranspiration) over the heterogeneous landscape[J].Plateau Meteorology,1997,16(4): 446-452.[马耀明,王介民. 非均匀陆面上区域蒸发(散)研究概况[J]. 高原气象, 1997,16(4): 447-452.]
[2] Guo Xiaoyin,Cheng Guodong.Advances in the application of remote sensing to evapotranspiration reserch[J].Advances in Earth Science, 2004, 19(1): 107-114.[郭晓寅, 程国栋. 遥感技术应用于地表蒸散发的研究进展[J]. 地球科学进展, 2004, 19(1): 107-114.]
[3] Li Xin,Ma Mingguo,Wang Jian,et al.Simultaneous remote sensing and ground-based experiment in the Heihe river basin:Scientific objectives and experiment design[J].Advances in Earth Science,2008,23(9):897-914.[李新,马明国,王建,等.黑河流域遥感一地面观测同步试验:科学目标与试验方案[J].地球科学进展,2008,23(9):897-914.]
[4] Blad B L, Rosenberg N J. Evaluation of resistance and mass transport evapotranspiration models requiring canopy temperature data[J].Agronorny Journal,1976, 68: 764-769.
[5] Hatfield J L, Reginato R J, Idso S B. Evaluation of canopy temperature evapotranspiration models over various crops[J]. Agriculture Meteor,1984, 32: 41-53.
[6] Choudhury B J, Reginato R J, Idso S B. An analysis of infrared temperature observations over wheat and calculation of the latent heat flux[J].Agriculture Meteor,1986, 37: 75-88.
[7] Ma Yaoming,Dai Youxue,Ma Weiqiang,et al.Satellite remote sensing parameterization of regional landsurface heat fluxes over heterogeneous surface of arid and semi-arid areas[J].Plateau Meteorology,2004,23(2):139-146.[马耀明,戴有学,马伟强,等. 干旱半干旱非均匀地表区域能量通量的卫星遥感参数化[J]. 高原气象,2004,23(2):139-146.]
[8] Ma Yaoming,Wang Jiemin.Estimation of flux densities over the heterogeneous land surface with the aid of satellite remote sensing and field observation[J].Acta Meteorologica Sinica,1999,57(2): 180-189.[马耀明,王介民. 卫星遥感结合地面观测估算非均匀地表区域能量通量[J].气象学报,1999,57(2): 180-189.]
[9] Xin Xiaozhou,Liu Qinhuo,Tang Yong,et al.Estimation of evapotranspiration using CBERS-02 and MODIS data[J].Science in China (Series E),2005,35(B12):125-140.[辛晓洲,柳钦火,唐勇,等.用CBERS-02卫星和MODIS数据联合反演地表蒸散通量[J].中国科学:E辑,2005,35(B12):125-140.]
[10] Kustas W P, Norman J M, Anderson M C, et al. Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship[J].Remote Sensing of Environment, 2003, 85(4): 429-440.
[11] Anderson M C,Norman J M,Mecikalski J R,et al. A multiscale remote sensing model for disaggregating regional fluxes to micrometeorological scales[J].Journal of Hydrometeorology, 2004, 5(2): 343-363.
[12] Liang S.Narrowband to broadband conversions of land surface albedo.I-Algorithms[J].Remote Sensing of Environment,2001,76(2):213-238.
[13] Liang S,Shuey C,Russ A,et al.Narrowband to broadband conversions of land surface albedo.II-Validation[J].Remote Sensing of Environment,2003,84(1):25-41.
[14] Qin Z,Kamieli A,BerUner P.A mono-window algorithm for retrieving land surface temperature from landsat TM data and its application to the Israel—Egypt border region[J].International Journal of Remote Sensing,2001,22(18):3 719-3 746.
[15] Van De Griend A A,Owe M.On the relationship between thermal emissivity and the normalize difference vegetation index for natural surfaces[J].International Journal of Remote Sensing,1993,14(6):1 119-1 131.
[16] Ballantine J A C,Okin G S,Prentiss D E,et al.Mapping north African landforms using continental scale unmixing of MODIS imagery[J].Remote Sensing of Environment,2005,97(4):470-483.
[17] Conrad C,Dech S W,Hafeez M,et al. Mapping and assessing water use in a central Asian irrigation system by utilizing MODIS remote sensing products[J].Irrigation and Drainage Systems,2007, 21(3/4):197-218.
[18] Malliek K,Bhattacharya B K,Chaurasia S,et al. Evapotranspiration using MODIS data and limited ground observations over selected agroecosystems in India[J].International Journal of Remote Sensing,2007, 28(10): 2 091-2 110.
[19] Xu Ziwei,Liu Shaomin,Gong Lijuan,et al.Processing and quality assessment of eddy covariance system data[J].Advances in Earth Science,2008,23(4):357-370.[徐自为,刘绍民,宫丽娟,等.涡动相关仪观测数据的处理与质量评价研究[J].地球科学进展,2008,23(4):357-370.]
[20] Lu Li,Liu Shaomin,Xu Ziwei,et al.Results from measurements of large aperture seintillometer over different surfaces[J].Journal of Applied Meteorological Science,2009,20(2):171-178.[卢俐,刘绍民,徐自为,等.不同下垫面大孔径闪烁仪观测数据处理与分析[J].应用气象学报,2009,20(2):171-178.]
[21] Chen Yunhao,Li Xiaobing,Shi Peijun.The remote sensing model for regional evapotranspiration estimation over heterogeneous landscape[J].Acta Meteorologica Sinica,2002,60(4):508-512.[陈云浩,李晓兵,史培军.非均匀陆面条件下区域蒸散量计算的遥感模型[J].气象学报,2002,60(4):508-512.]
[22] Su Z.The Surface Energy Balance System(SEBS)for estimation of turbulent heat fluxes[J].Hydrology and Earth System Sciences,2002,6(1):85-99.
[23] Chen Yunhao,Li Xiaobing,Li Jing,et al.Estimation of daily evapotranspiration using a two-layer remote sensing model[J].International Journal of Remote Sensing,2005,26(8):1 755-1 762.
[24] Choudhury B J,Reginato R J,Idso S B. An analysis of infrared temperature observations over wheat and calculation of latent heat fluxes[J].Agricultural and Forest Meteorology,1986,37:75-88.
[25] Huband N D S, Monteith J L. Radiative surface temperature and energy balance of a wheat canopy:I.Comparison of radiative and aerodynamic canopy temperature[J].Boundary-Layer Meceorology,1986,36:1-17.
[26] Kustas W P. Estimates of evapotranspiration with a one-and two-layer model of heat transfer over partial canopy cover[J]. Journal of Meteorological Application,1990,29: 704-715.
[27] Chen Jingming. A critical fault in currently used remote-sensing evapotranspiration models and its correction[J].Chinese Science Bulletin, 1988,6:454-457.[陈镜明. 现用遥感蒸散模式中的一个重要缺点及改进[J].科学通报, 1988,6:454-457.]
/
〈 |
|
〉 |