Chlorophyll content retrieve of vegetation using Hyperion data based on empirical models
FENG Mingbo1,2,3, NIU Zheng1,2
1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
2. The State Key Laboratory of Remote Sensing Science, Chinese Academy of Sciences, Beijing 100101, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China
Modeling using empirical methods based on Hyperion is a fast and accurate way to retrieve vegetation chlorophyll content. In this paper,the measured spectra and simulated Hyperion spectra were analyzed,the correlation between chlorophyll content and reflectance with its change forms and the relation between chlorophyll content and red edge parameters as well as vegetation indexes were calculated to obtain the most accurate modeling method. The vegetation index of modified simple ratio(MSR)has a significant correlation with chlorophyll content,and its regression model can retrieve chlorophyll concentration accurately. Using MSR and measured chlorophyll content,the authors built the regression model based on Hyperion data and then established the chlorophyll concentration profile. The chlorophyll concentration profile of Zhangye City was computed and a high-accuracy was achieved,with its relative error less than 5%.
丰明博, 牛铮. 基于经验模型的Hyperion数据植被叶绿素含量反演[J]. 国土资源遥感, 2014, 26(1): 71-77.
FENG Mingbo, NIU Zheng. Chlorophyll content retrieve of vegetation using Hyperion data based on empirical models. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(1): 71-77.
[1] Curran P J, Dungan J L, Gholz H L.Exploring the relationship between reflectance red edge and chlorophyll content in slash pine[J].Tree Physiol, 1990, 7(1/4):33-38.[2] Gitelson A A, Merzlyak M N.Signature analysis of leaf reflectance spectra:Algorithm development for remote sensing[J].Plant Physiol, 1996, 148(3/4):493-500.[3] Jacquemoud S, Ustin S L, Verdebout J, et al.Estimating leaf biochemistry using the PROSPECT leaf optical properties model[J].Remote Sensing of Environment, 1996, 56(3):194-202[4] Wessman C A, Aber J D, Peterson D L.An evaluation of imagings spectrometry for estimating forest canopy chemistry[J].International Journal of Remote Sensing, 1989, 10(8):1293-1316.[5] Peñuelas J, Filella I, Gamon J A.Assessment of photosynthetic radiation-use efficiency with spectral reflectance[J].New Phytol, 1995, 131(3):291-296.[6] 吴朝阳, 牛铮.植物光化学植被指数对叶片生化组分参数的敏感性[J].中国科学院研究生院学报, 2008, 25(3):346-354. Wu C Y, Niu Z.Sensitivity study of photochemical reflectance index to leaf biochemical components[J].Journal of the Graduate School of the Chinese Academy of Sciences, 2008, 25(3):346-354.[7] 吴朝阳, 牛铮.基于辐射传输模型的高光谱植被指数与叶绿素浓度及叶面积指数的线性关系改进[J].植物学通报, 2008, 25(6):714-721. Wu C Y, Niu Z.Improvement in linearity between hyperspectral vegetation indices and chlorophyll content, leaf area index based on radiative transfer models[J].Chinese Bulletin of Botany, 2008, 25(6):714-721.[8] 方慧, 宋海燕, 曹芳, 等.油菜叶片的光谱特征与叶绿素含量之间的关系研究[J].光谱学与光谱分析, 2007, 27(9):1731-1734. Fang H, Song H Y, Cao F, et al.Study on the relationship between spectral properties of oilseed rape leaves and their chlorophyll content[J].Spectroscopy and Spectral Analysis, 2007, 27(9):1731-1734.[9] Pinar A, Curran P J.Technical note grass chlorophyll and the reflectance red edge[J].International Journal of Remote Sensing, 1996, 17(2):351-357.[10] Gitelson A, Merzlyak M N.Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L.and Acer platanoides L.leaves.spectral features and relation to chlorophyll estimation[J].Journal of Plant Physiology, 1994, 143(3), 286-292.[11] Chen J.Evaluation of vegetation indices and modified simple ratio for boreal applications[J].Canadian Journal of Remote Sensing, 1996, 22:229–242.[12] Daughtry C S T, Walthall C L, Kim M S, et al.Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance[J].Remote Sensing of Environment, 2000, 74(2):229-239.[13] Rondeaux G, Steven M, Baret F.Optimization of soil-adjusted vegetation indices[J].Remote Sensing of Environment, 1996, 55(2):95–107.[14] Curran P J.Remote sensing of foliar chemistry[J].Remote Sensing of Environment, 1989, 30(3):271-278.[15] Rouse J W, Haas R H, Schell J A, et al.Monitoring the vernal advancements and retrogradation(greenwave effect)of natural vegetation[R].NASA/GSFC, Final Report, Greenbelt, MD, USA, 1974:1-137.[16] 陈君颖, 田庆久, 亓雪勇, 等.基于Hyperion影像的水稻冠层生化参量反演[J].遥感学报, 2009, 13(6):1106-1121. Chen J Y, Tian Q J, Qi X Y, et al.Rice canopy biochemical concentration retrievals based on Hyperion data[J].Journal of Remote Sensing, 2009, 13(6):1106-1121.[17] 鞠昌华, 田永超, 朱艳, 等.小麦叠加叶片的叶绿素含量光谱反演研究[J].麦类作物学报, 2008, 28(6):1068-1074. Ju C H, Tian Y C, Zhu Y, et al.Spectral inverse study of stacked leaf chlorophyll concentration in wheat[J].Journal of Triticeae Crops, 2008, 28(6):1068-1074.[18] 杨敏华, 刘良云, 刘团结, 等.小麦冠层理化参量的高光谱遥感反演试验研究[J].测绘学报, 2002, 31(4):316-321. Yang M H, Liu L Y, Liu T J, et al.Research on a method to retrieve biophysical and biochemical parameters of wheat canopy with hyperspectral remote sensing[J].Acta Geodaetica et Cartographica Sinica, 2002, 31(4):316-321.[19] 颜春燕.遥感提取植被生化组分信息方法与模型研究[D].北京:中国科学院遥感应用研究所, 2004. Yan C Y.Study on methods and models for vegetation biochemical information retrieval by remote sensing[D].Beijing:Institute of Remote Sensing Applications, Chinese Academy of Sciences, 2004.
2014, Vol. 26 
