浏览全部资源
扫码关注微信
纸质出版日期： 2019-7 ，
录用日期： 2018-4-11
扫 描 看 全 文
何丹丹, 焦子锑, 董亚冬, 张小宁, 张虎, 丁安心. 2019. 机载WIDAS地表观测的BRDF原型反演算法验证. 遥感学报, 23(4): 620–629
He D D, Jiao Z T, Dong Y D, Zhang X N, Zhang H and Ding A X. 2019. Verification of BRDF archetype inversion algorithm from surface observations of airborne WIDAS. Journal of Remote Sensing, 23(4): 620–629
地表反照率表征地面对太阳辐射的反射能力，在地表能量平衡中起着重要的作用。2008年黑河的WATER实验中，针对机载红外广角双模式成像仪(WIDAS)观测角度小的特点，发展了一种基于MODIS二向性反射分布函数(BRDF)原型估算WIDAS反照率的算法。然而，在2012年黑河HiWATER实验中，WIDAS的观测角度范围由早期30°观测天顶角升级为最大观测天顶角52°，这一改造对数据预处理(辐射定标、大气校正和多角度配准)产生影响，使WIDAS数据出现明显的噪声，为WIDAS地表反照率的反演带来新挑战。针对新问题，采用新的地表观测数据，进一步验证了BRDF原型算法反演机载WIDAS反照率的能力。为了获取准实时BRDF先验知识，基于核驱动模型和各向异性平整指数(AFX)首先准实时提取了实验区5种MODIS的BRDF原型；然后，将其作为先验知识应用到黑河WIDAS机载数据的反照率反演中；最后，利用实验区的反照率实测数据进行算法验证。本研究比较了3个算法处理该问题的能力：(1)基于BRDF原型作为先验知识的算法；(2)完全基于核驱动的全反演算法；(3)基于朗伯假设的方法，通过算法对比分析，可更好地分析验证算法(1)的性能。结果表明：(1)BRDF原型算法反演精度最高且稳定，尤其是当观测数据位于垂直主平面时，全反演算法由于缺少大角度观测数据的约束，更容易出现异常值；BRDF原型算法的最大绝对误差为0.034，相对于全反演算法和朗伯假设方法精度分别提高了约18%和71%；(2)针对2012年黑河机载WIDAS观测噪声较大的新问题，BRDF原型反演算法表现出了良好的抗噪声性能。通过对WIDAS反照率反演和验证进一步表明，在多角度观测数据信息量不足以进行全反演，且观测受噪声影响较大时，BRDF原型作为先验知识，提供了一种有效解决该问题的手段，对提高反照率反演的精度、增强反演的稳定性有重要作用。
Surface albedo qualifies the proportion of incoming light reflected by the land surface and plays an important role in the earth’s energy budget. In the WATER experiment of Heihe in 2008
we developed an algorithm for estimating the albedo of Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) based on the MODIS Bidirectional Reflection Distribution Function (BRDF) archetype-based algorithm for the narrow-angle observations of the airborne WIDAS. However
in the HiWATER experiment in 2012
the WIDAS observation angle range was upgraded from the early 30° to the maximum observation zenith angle of 52°
which impacted the data preprocessing (radiation scaling
atmospheric correction
and multi-angle registration). This condition caused significant noise and created new challenges for the surface albedo inversion of WIDAS. In the current study
we addressed new problems and adopted new surface observation data to verify the ability of the BRDF archetype-based algorithm to retrieve the albedo of WIDAS. To obtain quasi-real-time BRDF prior knowledge
we first extracted five BRDF archetypes as a priori information from 500 m MODIS BRDF parameter product (MCD43A1) within the Heihe experimental region. Then
we applied these BRDF archetypes to airborne WIDAS multi-angular observations for albedo estimates based on the hotspot-corrected linear kernel-driven BRDF model
that is
RossThickChen-LiSparseReciprocal model. Finally
field albedo measurements were conducted to validate the broadband albedo estimates. We compared three commonly used albedo estimate methods
namely
the BRDF archetype-based algorithm that was developed in our previous paper; full-inversion BRDF/albedo algorithm that has been adopted as the operational MODIS BRDF/albedo algorithm; and Lambertian assumption method that is commonly used to estimate surface albedo
especially when only nadir observations are available. The performance of the BRDF archetype-based algorithm was verified by comparison and analysis of the algorithms. Unsurprisingly
the accuracy of the albedo retrievals by using the BRDF archetype-based algorithm was obtained at 0.034
which was 18% and 71% higher than those of the full inversion algorithm and the Lambertian assumption method
respectively. The inversion and verification of the WIDAS demonstrated that the BRDF archetype-based method was noise resistant and obtained stable albedo estimates. Therefore
our previous conclusions were confirmed by using new WIDAS observations. Given the merit of the proposed archetype-based algorithm
we strongly recommend it to the user community
especially for narrow-angle observations that need a priori information for stable retrievals of surface albedo.
遥感黑河MODIS机载WIDAS核驱动模型AFXBRDF原型地表反照率
remote sensingHeiheMODISWide-angle Infrared Dual-mode line/area Array Scanner (WIDAS)kernel-driven BRDF modelAFXBRDF archetypesurface albedo
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
Bréon F M, Maignan F, Leroy M and Grant I. 2002. Analysis of hot spot directional signatures measured from space. Journal of Geophysical Research: Atmospheres, 107(D16): 4282
Chen J M and Cihlar J. 1997. A hotspot function in a simple bidirectional reflectance model for satellite applications. Journal of Geophysical Research: Atmospheres, 102(D22): 25907–25913
Dickinson R E. 1983. Land surface processes and climate—surface albedos and energy balance. Advances in Geophysics, 25: 305–353
董亚冬, 焦子锑, 张虎, 李佳悦, 焦广平, 石涵予. 2014. 改善MODIS BRDF产品热点效应的方法研究. 遥感学报, 18(4): 804–825
Dong Y D, Jiao Z T, Zhang H, Li J Y, Jiao G P and Shi H Y. 2014. Efficient algorithm for improving the hotspot effect of the operational MODIS BRDF product. Journal of Remote Sensing, 18(4): 804–825
Dong Y D, Jiao Z T, Zhang H, Bai D N, Zhang X N, Li Y and He D D. 2016. A visualization tool for the kernel-driven model with improved ability in data analysis and kernel assessment. Computers and Geosciences, 95: 1–10
Jiao Z T, Hill M J, Schaaf C B, Zhang H, Wang Z S and Li X W. 2014. An anisotropic flat index (AFX) to derive BRDF archetypes from MODIS. Remote Sensing of Environment, 141: 168–187
焦子锑, 李小文, 王锦地, 张虎. 2011. 评估MODIS的BRDF角度指数产品. 遥感学报, 15(3): 432–456
Jiao Z T, Li X W, Wang J D and Zhang H. 2011. Assessment of MODIS BRDF shape indicators. Journal of Remote Sensing, 15(3): 432–456
Jiao Z T, Schaaf C B, Dong Y D, Román M, Hill M J, Chen J M, Wang Z S, Zhang H, Saenz E, Poudyal R, Gatebe C, Bréon F M, Li X W and Strahler A. 2016. A method for improving hotspot directional signatures in BRDF models used for MODIS. Remote Sensing of Environment, 186: 135–151
Jiao Z T, Zhang H, Dong Y D, Liu Q, Xiao Q and Li X W. 2015. An algorithm for retrieval of surface albedo from small view-angle airborne observations through the use of BRDF archetypes as prior knowledge. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(7): 3279–3293
Jiao Z T, Zhang H and Li X W. 2012. To derive a prior database of archetypal BRDF shapes from ground measurements using anisotropic flat index (AFX)//Proceedings of 2012 IEEE International Geoscience and Remote Sensing Symposium. Munich, Germany: IEEE: 6753-6756 [DOI: 10.1109/IGARSS.2012.6352555]
Jin Y F, Schaaf C B, 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: 1. Algorithm performance. Journal of Geophysical Research: Atmospheres, 108(D5): 4158
Li X, Li X W, Li Z Y, Ma M G, Wang J, Xiao Q, Liu Q, Che T, Chen E X, Yan G J, Hu Z Y, Zhang L X, Chu R Z, Su P X, Liu Q H, Liu S M, Wang J D, Niu Z, Chen Y, Jin R, Wang W Z, Ran Y H, Xin X Z and Ren H Z. 2009. Watershed allied telemetry experimental research. Journal of Geophysical Research: Atmospheres, 114(D22): D22103
李小文. 1989. 地物的二向性反射和方向谱特征. 环境遥感, 4(1): 67–72
Li X W. 1989. Bidirectional reflectance and angular signature of objects. Remote Sensing of Environment China, 4(1): 67–72
Li X W, Gao F, Chen L Z and Strahler A H. 1999. Derivation and validation of a new kernel for kernel-driven BRDF models//Proceedings of the Remote Sensing for Earth Science, Ocean, and Sea Ice Applications. Florence, Italy: SPIE: 368-379 [DOI: 10.1117/12.373123]
Li X W, Gao F, Wang J D and Strahler A. 2001. A priori knowledge accumulation and its application to linear BRDF model inversion. Journal of Geophysical Research: Atmospheres, 106(D11): 11925–11935
李新, 刘绍民, 马明国, 等. 2012. 黑河流域生态—水文过程综合遥感观测联合试验总体设计. 地球科学进展, 27(5): 481–498
Li Xin, Liu Shaomin, Ma Mingguo, et al. 2012. HiWATER: An integrated remote sensing experiment on hydrological and ecological processes in the Heihe River Basin. Advances in Earth Science, 27(5): 481–498
Liang S L. 2001. Narrowband to broadband conversions of land surface albedo I: algorithms. Remote Sensing of Environment, 76(2): 213–238
Liu Q, Wang L Z, Qu Y, Liu N F, Liu S H, Tang H R and Liang S L. 2013. Preliminary evaluation of the long-term glass albedo product. International Journal of Digital Earth, 6(S1): 69–95
Lucht W and Lewis P. 2000. Theoretical noise sensitivity of BRDF and albedo retrieval from the EOS-MODIS and MISR sensors with respect to angular sampling. International Journal of Remote Sensing, 21(1): 81–98
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
Nicodemus F E, Richmond J C, Hsia J J, Ginsberg I W and Limperis T. 1977. Geometrical Considerations and Nomenclature for Reflectance. Monograph Number 160. US Department of Commerce
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 L and Roy D. 2002. First operational BRDF, albedo nadir reflectance products from MODIS. Remote Sensing of Environment, 83(1/2): 135–148
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: Atmospheres, 100(D10): 21077–21089
You D Q, Wen J G, Liu Q, Liu Q H and Tang Y. 2014. The angular and spectral kernel-driven model: assessment and application. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(4): 1331–1345
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
相关作者
相关机构