机载WIDAS数据的Landsat卫星反照率初步验证
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摘要
随着精细化监测的需求,中高空间分辨率的地表反照率产品逐渐成为气候模型的主要输入。目前,中高空间分辨率反照率产品的验证主要基于地表站点的通量塔观测数据,区域机载飞行数据的验证依然相对较少。因此,本文基于区域机载数据验证Landsat反照率产品。针对内蒙古自治区根河森林试验区所获取的机载红外广角双模式成像仪(WIDAS)多角度反射率数据,应用BRDF原型反演算法估算其反照率,分析了应用机载数据验证中高空间分辨率反照率产品的潜力。2016年内蒙古根河森林试验区机载WIDAS飞行多角度观测的可用多角度范围为25°,以前的研究表明BRDF原型反照率反演算法表现出对小观测角度的反照率反演结果的鲁棒性。因此,机载WIDAS反照率在一定程度可用于星载反照率的验证。首先,基于核驱动模型和各向异性平整指数(AFX)提取了试验区4种MODIS二向性反射分布函数(BRDF)原型;然后,将其作为先验知识应用到根河森林WIDAS机载数据的反照率反演中;最后,用WIDAS反照率和单个地面通量塔观测的反照率对Landsat卫星数据的反照率进行初步验证。验证结果表明Landsat反照率与WIDAS反照率结果较为一致,但略有低估,总体均方根误差(RMSE)约为0.02,偏差为0.0057。在多角度观测范围较小时,BRDF原型的反照率反演算法可为星载地表反照率的验证提供了一种有效的验证手段。
Surface albedo is one of the key parameters in the investigation of surface energy balance. Accurate inversion of surface albedo is important for the evaluation on climate change. For the multi-angle reflectance data of an airborne Wide-angle Infrared Dual-mode line/area Array Scanner(WIDAS) in Genhe Region,Inner Mongolia, the Bidirectional Reflectance Distribution Function(BRDF) archetype-based algorithm was initially applied in forest experimental area. First, we extracted four BRDF archetypes based on the hotspot-corrected linear kernel-driven BRDF models, i.e., RossThickChen-LiSparseReciprocal and anisotropic flat index, in the experimental region of Genhe. Then, we applied these archetypes as a priori knowledge to the albedo inversion of WIDAS airborne data in the forest of the region. Finally, the albedo of WIDAS and the data observed by surface flux tower were used to verify Landsat albedo. In this study, we analyzed the robustness of the BRDF archetype-based algorithm in retrieving small-angle observations in forest experimental area. The results are as follows.(1) The surface albedo retrieved by the BRDF archetype-based algorithm has high accuracy and stability, and the total Root Mean Square Error(RMSE) of Landsat albedo was approximately 0.02 and deviation was 0.0057.(2) Given the available observation range of WIDAS in the experimental area of Genhe in 2016 was 25°, the BRDF archetype-based algorithm showed robust inversion capability in small observation angles. Therefore, when the multi-angle observation range was narrow, the albedo of airborne WIDAS retrieved by the BRDF archetype-based algorithm can be in good agreement with that of the Landsat, providing a means to effectively address the problem and validate the satellite albedo.
Surface albedo is one of the key parameters in the investigation of surface energy balance. Accurate inversion of surface albedo is important for the evaluation on climate change. For the multi-angle reflectance data of an airborne Wide-angle Infrared Dual-mode line/area Array Scanner(WIDAS) in Genhe Region,Inner Mongolia, the Bidirectional Reflectance Distribution Function(BRDF) archetype-based algorithm was initially applied in forest experimental area. First, we extracted four BRDF archetypes based on the hotspot-corrected linear kernel-driven BRDF models, i.e., RossThickChen-LiSparseReciprocal and anisotropic flat index, in the experimental region of Genhe. Then, we applied these archetypes as a priori knowledge to the albedo inversion of WIDAS airborne data in the forest of the region. Finally, the albedo of WIDAS and the data observed by surface flux tower were used to verify Landsat albedo. In this study, we analyzed the robustness of the BRDF archetype-based algorithm in retrieving small-angle observations in forest experimental area. The results are as follows.(1) The surface albedo retrieved by the BRDF archetype-based algorithm has high accuracy and stability, and the total Root Mean Square Error(RMSE) of Landsat albedo was approximately 0.02 and deviation was 0.0057.(2) Given the available observation range of WIDAS in the experimental area of Genhe in 2016 was 25°, the BRDF archetype-based algorithm showed robust inversion capability in small observation angles. Therefore, when the multi-angle observation range was narrow, the albedo of airborne WIDAS retrieved by the BRDF archetype-based algorithm can be in good agreement with that of the Landsat, providing a means to effectively address the problem and validate the satellite albedo.
引文
Dickinson R E.1983.Land surface processes and climate-surface albedos and energy balance.Advances in Geophysics,25:305-353[DOI:10.1016/S0065-2687(08)60176-4]
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[DOI:10.1016/j.cageo.2016.06.010]
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(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)[DOI:10.11834/jrs.20143229]
Hu Y,Liu L Y,Liu L L,Peng D L,Jiao Q J and Zhang H.2014.Alandsat-5 atmospheric correction based on MODIS atmosphere products and 6s model.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,7(5):1609-1615[DOI:10.1109/JSTARS.2013.2290028]
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[DOI:10.1016/j.rse.2013.10.017]
Jiao Z T,Li X W,Wang J D and Zhang H.2011.Assessment of MOD-IS BRDF shape indicators.Journal of Remote Sensing,15(3):432-456(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,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[DOI:10.1109/JSTARS.2015.2414925]
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)//2012 IEEE International Geoscience and Remote Sensing Symposium.Munich:IEEE:6753-6756[DOI:10.1109/IGARSS.2012.6352555]
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[DOI:10.1029/2000JD900639]
Liang S L.2001.Narrowband to broadband conversions of land surface albedo I:algorithms.Remote Sensing of Environment,76(2):213-238[DOI:10.1016/S0034-4257(00)00205-4]
Liang S L,Shuey C J,Russ A L,Fang H L,Chen M Z,Walthall C L,Daughtry C S T and Hunt R Jr.2003.Narrowband to broadband conversions of land surface albedo:II.Validation.Remote Sensing of Environment,84(1):25-41[DOI:10.1016/S0034-4257(02)00068-8]
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[DOI:10.1109/36.841980]
Masek J G,Vermote E F,Saleous N E,Wolfe R,Hall F G,Huemmrich K F,Gao F,Kutler J and Lim T K.2006.A Landsat surface reflectance dataset for North America,1990-2000.IEEE Geoscience and Remote Sensing Letters,3(1):68-72[DOI:10.1109/LGRS.2005.857030]
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(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)[DOI:10.11834/jrs.20133118]
Román M O,Schaaf C B,Woodcock C E,Strahler A H,Yang X Y,Braswell R H,Curtis P S,Davis K J,Dragoni D,Goulden M L,Gu L H,Hollinger D Y,Kolb T E,Meyers T P,Munger J W,Privette J L,Richardson A D,Wilson T B and Wofsy S C.2009.The MODIS(collection V005)BRDF/albedo product:assessment of spatial representativeness over forested landscapes.Remote Sensing of Environment,113(11):2476-2498[DOI:10.1016/j.rse.2009.07.009]
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[DOI:10.1016/S0034-4257(02)00091-3]
Shuai Y,Masek J G,Gao F and Schaaf C B.2011.An algorithm for the retrieval of 30-m snow-free albedo from Landsat surface reflectance and MODIS BRDF.Remote Sensing of Environment,115(9):2204-2216[DOI:10.1016/j.rse.2011.04.019]
Wang Y J,Liu L Y,Hu Y,Li D H and Li Z Q.2016.Development and validation of the landsat-8 surface reflectance products using a MODIS-based per-pixel atmospheric correction method.International Journal of Remote Sensing,37(6):1291-1314[DOI:10.1080/01431161.2015.1104742]
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[DOI:10.1029/95JD02371]
Xu H Q.2015.Retrieval of the reflectance and land surface temperature of the newly-launched Landsat 8 satellite.Chinese Journal of Geophysics,58(3):741-747(徐涵秋.2015.新型Landsat8卫星影像的反射率和地表温度反演.地球物理学报,58(3):741-747)[DOI:10.6038/cjg20150304]
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,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)[DOI:10.11834/jrs.20133022]
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[DOI:10.1016/j.cageo.2016.06.010]
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(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)[DOI:10.11834/jrs.20143229]
Hu Y,Liu L Y,Liu L L,Peng D L,Jiao Q J and Zhang H.2014.Alandsat-5 atmospheric correction based on MODIS atmosphere products and 6s model.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,7(5):1609-1615[DOI:10.1109/JSTARS.2013.2290028]
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[DOI:10.1016/j.rse.2013.10.017]
Jiao Z T,Li X W,Wang J D and Zhang H.2011.Assessment of MOD-IS BRDF shape indicators.Journal of Remote Sensing,15(3):432-456(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,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[DOI:10.1109/JSTARS.2015.2414925]
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)//2012 IEEE International Geoscience and Remote Sensing Symposium.Munich:IEEE:6753-6756[DOI:10.1109/IGARSS.2012.6352555]
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[DOI:10.1029/2000JD900639]
Liang S L.2001.Narrowband to broadband conversions of land surface albedo I:algorithms.Remote Sensing of Environment,76(2):213-238[DOI:10.1016/S0034-4257(00)00205-4]
Liang S L,Shuey C J,Russ A L,Fang H L,Chen M Z,Walthall C L,Daughtry C S T and Hunt R Jr.2003.Narrowband to broadband conversions of land surface albedo:II.Validation.Remote Sensing of Environment,84(1):25-41[DOI:10.1016/S0034-4257(02)00068-8]
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[DOI:10.1109/36.841980]
Masek J G,Vermote E F,Saleous N E,Wolfe R,Hall F G,Huemmrich K F,Gao F,Kutler J and Lim T K.2006.A Landsat surface reflectance dataset for North America,1990-2000.IEEE Geoscience and Remote Sensing Letters,3(1):68-72[DOI:10.1109/LGRS.2005.857030]
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(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)[DOI:10.11834/jrs.20133118]
Román M O,Schaaf C B,Woodcock C E,Strahler A H,Yang X Y,Braswell R H,Curtis P S,Davis K J,Dragoni D,Goulden M L,Gu L H,Hollinger D Y,Kolb T E,Meyers T P,Munger J W,Privette J L,Richardson A D,Wilson T B and Wofsy S C.2009.The MODIS(collection V005)BRDF/albedo product:assessment of spatial representativeness over forested landscapes.Remote Sensing of Environment,113(11):2476-2498[DOI:10.1016/j.rse.2009.07.009]
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[DOI:10.1016/S0034-4257(02)00091-3]
Shuai Y,Masek J G,Gao F and Schaaf C B.2011.An algorithm for the retrieval of 30-m snow-free albedo from Landsat surface reflectance and MODIS BRDF.Remote Sensing of Environment,115(9):2204-2216[DOI:10.1016/j.rse.2011.04.019]
Wang Y J,Liu L Y,Hu Y,Li D H and Li Z Q.2016.Development and validation of the landsat-8 surface reflectance products using a MODIS-based per-pixel atmospheric correction method.International Journal of Remote Sensing,37(6):1291-1314[DOI:10.1080/01431161.2015.1104742]
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[DOI:10.1029/95JD02371]
Xu H Q.2015.Retrieval of the reflectance and land surface temperature of the newly-launched Landsat 8 satellite.Chinese Journal of Geophysics,58(3):741-747(徐涵秋.2015.新型Landsat8卫星影像的反射率和地表温度反演.地球物理学报,58(3):741-747)[DOI:10.6038/cjg20150304]
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,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)[DOI:10.11834/jrs.20133022]