收稿：2016-11-17，
录用：2017-9-26，
纸质出版：2018-03
移动端阅览
地表反照率(Albedo)是描述地表辐射能量平衡的重要参数，为了获得高分四号(GF-4)静止卫星的地表反照率产品，构建了一种基于核驱动双向反射率分布(BRDF)模型的反照率反演方法。首先，探索核驱动BRDF模型对GF-4卫星数据的适用性，加入地表分类信息，为核系数赋初值，并引入鲍威尔迭代算法优化模型结果。然后，对BRDF模型进行角度积分获得各个波段的地表窄波段反照率。在此基础上，结合GF-4卫星光谱响应函数与光谱库，首次建立了将窄波段反照率到宽波段反照率的转换系数，并反演得到0.4—0.7 μm和0.3—3.0 μm的宽波段反照率。最后，利用Landsat 8卫星数据和MODIS地表反照率产品对基于GF-4卫星数据的地表反照率反演结果进行交叉验证。Landsat 8与GF-4的反照率结果对比表明，GF-4卫星可见光范围内的反照率反演结果精度为85.6%，短波范围内的反照率反演结果精度为93.4%；MODIS与GF-4的反照率结果对比表明，可见光范围的地表反照率精度达到87.7%，短波范围的地表反照率精度达到85.9%。这说明GF-4卫星地表反照率反演结果具有较高精度，GF-4卫星反照率产品具有一定应用潜力。
Land surface albedo is an important surface parameter applied in surface energy balance. GF-4
which is the first geostationary orbit satellite that combines high spatial and temporal resolution in China
has great potential in obtaining regional albedo in the country. The present geostationary orbit satellites are relatively low in spatial resolution
and the observation ranges of most cannot cover all land areas because their orbitals are deviated from China. Multi-frequency observation cannot be easily realized in the country. Therefore
to address the problemsof short time and low spatial resolution of albedo products in China and obtain the albedo images of geostationary orbit satellite data
an albedo inversion method based on kernel-driven bidirectional reflectance distribution (BRDF)
taking GF-4 stationary satellite data as data source
is constructed. Earth surface classification is integrated to provide an initial value to kernel factorsto explore the feasibility of semi-empirical kernel-driven BRDF model applied on GF-4 satellite data. Compared with the least squares fitting method
the Powell iterative optimization algorithm has better convergence effect and is thus used to optimize the result of the model. Then
the land surface narrowband albedos of each band can be gained through angle integration using the BRDF model. Therefore
narrowbandalbedo is converted into broadband for the GF-4 satellite data for the first time by using the Santa Barbara DISORT model and combining the spectral library with the spectral response function of the GF-4 satellite. Albedo inversion in visible (0.4—0.7 μm) and shortwave bands (0.3—3 μm) are acquired. Finally
a cross-validation experiment using Landsat8 reflectivity and MODIS albedo productsis conducted. The albedo comparison results retrieved by Landsat8 and GF-4 data shows that the accuracy of albedo in the visible band retrieved by GF-4 data is 85.6%
and that in the shortwave band retrieved by GF-4 is 93.4%. The albedo comparison results retrieved by MODIS and GF-4 data shows that the accuracy of albedo in the visible band retrieved by GF-4 data is 87.7%
and that in shortwave band retrieved by GF-4 data is 85.9%. The experiment indicates that albedo retrieved by GF-4 data has high accuracy
and GF-4 satellite albedo products have considerable potential applications. The algebraic inversion method that uses GF-4 satellite data successfully obtains high-resolution albedo imagesfrom a geosynchronous orbit satellite. If this method is further verified
then it can be used for the mass production of albedo products and address the problemsof short time and low spatial resolution. However
relevant verification work should be conducted due to the current lack of ground test data.
Bacour C and Bréon F M. 2005. Variability of biome reflectance directional signatures as seen by POLDER. Remote Sensing of Environment, 98(1): 80–95
Berk A, Bernstein L Sand Robertson D C. 1989.MODTRAN: A Moderate Resolution Model for LOWTRAN 7.GL-TR-89-0122.
Dickinson R E. 1983. Land surface processes and climate-surface albedos and energy balance. Advances in Geophysics, 25: 305–353
Dickinson R E. 1995. Land processes in climate models. 1995. Remote Sensing of Environment, 51(1): 27–38
Friedl M A and Brodley C E. 1997. Decision tree classification of land cover from remotely sensed data. Remote Sensing of Environment, 61(3): 399–409
Hu B X, Lucht W, Li X W and Strahler A H. 1997. Validation of kernel-drivensemiempiricalmodels for the surface bidirectional reflectance distribution function of land surfaces. Remote Sensing of Environment, 62(3): 201–214
Jin Y F, Schaaf C B, Woodcock C E, Gao F, Li X W, Strahler A H, Lucht W and Liang S L. 2003. Consistency of MODIS surface bidirectional reflectance distribution function and albedo retrievals: 2. Validation.Journal of Geophysical Research, 108(D5): 4159
Kimes D S and Sellers P J. 1985. Inferring hemispherical reflectance of the earth’s surface for global energy budgets from remotely sensed nadir or directional radiance values. Remote Sensing of Environment, 18(3): 205–223
Kneizys F X, Shettle E P, Gallery W O, Chetwynd J H Jr, Abreu L W, Selby J E A, Clough S Aand Fenn R W. 1983. Atmospheric Transmittance/Radiance: Computer Code LOWTRAN 6. Supplement: Program Listings.Air force geophysics LAB Hanscomair force base, MA 01731-5000
Lewis P and Barnsley M J. 1994. Influence of the sky radiance distribution on various formulations of the earth surface albedo//Proceedings ofthe 6thInternationalSymposium on PhysicalMeasurements and Signaturesin Remote Sensing. Val d’Isere, France: ISPRS: 707–715
李乔亮, 汪国有, 刘建国, 陈少波. 2009. 基于样条金字塔和互信息的快速图像配准. 计算机应用研究, 26(5): 1949–1950, 1960
Li Q L, Wang G Y, Liu J G and Chen S B. 2009. Fast image registration based on spline pyramid and mutual information. Application Research of Computers, 26(5): 1949–1950, 1960 (
李小文, StrahlerA, 朱启疆, 刘毅, 刘广成, 张仁华, 虞献平, 李继泉. 1991. 地物二向性反射几何光学模型和观测的进展. 国土资源遥感, 3(1): 9–19
Li X W, StrahlerA, Zhu Q J, Liu Y, Liu G C, Zhang R H, Yu X P and Li J Q. 1991. Geometric-optical bidirectional reflectance modelling of ground objects and its progress in measurement. Remote Sensing for Land and Resources, 3(1): 9–19 (
李小文, 王锦地. 1995. 植被光学遥感模型与植被结构参数化. 北京: 科学出版社
Li X W and Wang J D. 1995. Vegetation Optical Remote Sensing Model and Vegetation Structure Paramerization. Beijing: Science Press
Liang S L. 2001. Narrowband to broadband conversions of land surface albedo I:Algorithms. Remote Sensing of Environment, 76(2): 213–238
Lucht W, Schaaf C B and Strahler A H. 2000. An algorithm for the retrieval of albedo from space using semiempirical BRDF models. IEEE Transactions on Geoscience and Remote Sensing, 38(2): 977–998
Pluim JPW, Maintz JBA and Viergever MA. 2003. Mutual-information-based registration of medical images: a survey. IEEE Transactions on Medical Imaging, 22(8): 986–1004
齐文栋, 刘强, 洪友堂. 2014. 3种反演算法的地表反照率遥感产品对比分析. 遥感学报, 18(3): 559–572
Qi W D, Liu Q and Hong Y T. 2014. Comparison analysis based on different inverse algorithms of surface albedo products. Journal of Remote Sensing, 18(3): 559–572 (
Ricchiazzi P, Yang S R, Gautier C and Sowle D. 1998. SBDART: a research and teaching software tool for plane-parallel radiative transfer in the Earth’s atmosphere. Bulletin of the American Meteorological Society, 79(10): 2101–2114
Roujean J L, Leroy M and Deschamps P Y. 1992. A bidirectional reflectance model of the earth’s surface for the correction of remote sensing data. Journal of Geophysical Research, 97(D18): 20455–20468
Schaaf C B, Gao F, Strahler A H, Lucht W, Li X W, Tsang T, Strugnell N C, Zhang X Y, Jin Y F, Muller J P, Lewis P, Barnsley M, Hobson P, Disney M, Roberts G, Dunderdale M, Doll C,d’Entremont R P, Hu B X, Liang S L, Privette J and Roy D. 2002. First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment, 83(1/2): 135–148
Shuai Y M, Schaaf C B, Strahler A H, Liu J C and Jiao Z T. 2008. Quality assessment of BRDF/albedo retrievals in MODIS operational system. Geophysical Research Letters, 35(5): L05407
Strugnell N C and Lucht W. 2001. An algorithm to infer continental-scale albedo from AVHRR data, land cover class, and field observations of typical BRDFs. Journal of Climate, 14(7): 1360–1376
Su J. 2010. Radiative Forcing Effect of Dust Aerosol over Northwestern China.Lanzhou:Lanzhou University
Wanner W, Li X and Strahler A H. 1995. On the derivation of kernels for kernel-driven models of bidirectional reflectance. Journal of Geophysical Research, 100(D10): 21077–21089
闻建光, 刘强, 柳钦火, 肖青,李小文.2015. 陆表二向反射特性遥感建模及反照率反演. 北京: 科学出版社: 199–200
Wen J G, Liu Q, Liu Q H, Xiao Q and Li X W. 2015. Remote Sensing Modeling of Surface Bidirectional Reflectance Characteristics and Retrieval of Albedo.Beijing: Science Press: 199–200
杨华, 李小文, 高峰. 2002. 新几何光学核驱动BRDF模型反演地表反照率的算法. 遥感学报, 6(4): 246–251
Yang H, Li X W and Gao F. 2002. An algorithm for the retrieval of albedo from space using new go kernel-driven BRDF model. Journal of Remote Sensing, 6(4): 246–251 (
张虎, 焦子锑, 董亚冬, 黄兴英, 李佳悦, 李小文. 2013. 基于BRDF原型反演地表反照率. 遥感学报, 17(6): 1475–1491
Zhang H, Jiao Z T, Dong Y D, Huang X Y, Li J Y and Li X W. 2013. An algorithm for retrieval albedo from BRDF archetype. Journal of Remote Sensing, 17(6): 1475–1491 (
张虎, 焦子锑, 董亚冬, 李佳悦, 李小文. 2015. 利用BRDF原型和单方向反射率数据估算地表反照率. 遥感学报, 19(3): 355–367
Zhang H, Jiao Z T, Dong Y D, Li J Y and Li X W. 2015. Albedo retrieved from BRDF archetype and surface directional reflectance. Journal of Remote Sensing, 19(3): 355–367 (
相关作者
相关机构
京公网安备11010802024621
