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利用统计和物理模型反演植物生化组分的比较

  • 阮伟利 ,
  • 牛铮
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  • 中国科学院遥感应用研究所遥感信息科学重点实验室, 北京 100101

收稿日期: 2003-04-21

  修回日期: 2003-05-26

  网络出版日期: 2004-01-10

基金资助

国家自然科学基金(40271086);国家重点基础研究发展规划项目(G2000077900);中国科学院知识创新工程重大项目(KZCX1SW01;KZCX2312)资助

Comparison of Retrieving Plant Biochemical Components with Statistical and Physical Models

  • Ruan Wei-li ,
  • Niu Zheng
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  • Key Laboratory of Remote Sensing Information Sciences, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China

Received date: 2003-04-21

  Revised date: 2003-05-26

  Online published: 2004-01-10

摘要

利用不同形式的光谱数据,如反射率、透射率和吸收率,以及经过不同波段间隔和噪声水平处理的反射率,直接比较了统计模型和物理模型反演鲜叶片叶绿素、水和干物质含量的效果。结果表明,物理模型对光谱数据波段间隔和噪声的鲁棒性比统计模型要好,而在反演的绝对效果上,统计模型的反演结果特别是对水分的反演与物理模型相当,要充分考虑统计模型和物理模型反演植物生化组分时的优缺点,提高反演的精度和效率。

本文引用格式

阮伟利 , 牛铮 . 利用统计和物理模型反演植物生化组分的比较[J]. 中国科学院大学学报, 2004 , 21(1) : 78 -83 . DOI: 10.7523/j.issn.2095-6134.2004.1.012

Abstract

Using reflectance,transmittance,absorptance and reflectance of different spectral interval and disturbed by noises,comparison is made between the effect of retrieving foliar biochemical components with statistical models and that with physical models. The result shows that the physical model is more robust to spectral interval and noises than the statistical model. However,as far as the real retrieving values are concerned,especially when it comes to the inversion of water in fresh leaves,the statistical model is as good as the physical model. So in order to improve precision and efficiency in retrieving plant biochemical components,statistical and physical models should be used according to the purpose of research.

参考文献

[1] Jacquemoud S,Ustin S L. Leaf optical properties:a state of the art. In:Pro. 8th International Symposium Physical Measurements Signatures in Remote Sensing. France:Aussois,2001.223-232

[2] Barbara) Y,Rita E Pettigrew-Crosby. Predicting nitrogen and chlorophyll content and concentrationsfrom reflectance spectra (400-2500nm) at leaf and canopy scales. Remote Sensing of Environment,1995,53:199-211

[3] 牛铮,陈永华,隋洪智,等.叶片化学组分成像光谱遥感探测机理分析.遥感学报,2000,4(2) : 125-130

[4] 吴长山,项月琴,郑兰芬,等.利用高光谱数据对作物群体叶绿素密度估算的研究.遥感学报,2000, 4(3) :228-232

[5] Jacquemoud S,Baret F. PROSPECT:A model of leaf optical proerties. Remote Sensing of Environment,1990,34 :75-91

[6] Jacquemoud S,Baret F,Andrieu B,Danson F M,Jaggard K. Extraction of vegetation biophysical parameters by inversion of thePROSPECT+SAIL models on sugar beet canopy reflectance data. Aapplication to TM and AVIRIS sensors. Remote Sensing of Environ-ment,1995,52:1G3-172

[7] Curran P J,Dungan J L,Peterson D L. Estimating the foliar biochemical concentration of leaves with reflectance spectrometry:Testingthe kokaly and Clark methodologies. Remote Sensing of Environment,2001,76:349-359

[8] YanCY,LiuQ,Niu Zh,et al. Estimating foliar chlorophyll concentration at leaf and canopy level:Testing and evaluating an empiricalmethodology. In:Proceedings of the First Quantitative Symposium on Remote Sensing.即ain,2002

[9] Jacquemoud S,Ustin S L,Verdebout J,Schmuck G, Andreoli G,Hosgood B. Estimating leaf biochemistry using the PROSPECT leaf op-tical properties model. Remote Sensing of Environment,1996,56:194-202

[10] Baret F,Fourty Th. Estimation of leaf water content and specific leaf weight from reflectance and transmittance measurements. A-gronomie,1997,17:455-464

[11] Hruschka W R. Data analysis: Wavelength selection methods. In:P C Williams,K H Norris. Near Infrared Technology in the Agricultraland Food Industries. (St Paul :American Association of Cereal Chemists,Inc.)1987.35-55

[12] 李云梅,王秀珍,沈掌泉,于军平,王人潮.水稻叶片反射率模拟.浙江大学学报(农业与生命科学版),2002,28 (2) : 195-198

[13] 颜春燕,蒋耿明,王成,牛铮,王长耀.植被单叶光谱特性的理沦模拟.遥感学报,2003,7(2) :81-85

[14] Hosgood B,Jacquemoud S,Andreoli G, Verdebout J,Pedrini G, Schmuck G. Leaf optical properties experiment 93 (LOPEX93) reportEU R-16096-EI\.European Commission,Joint Research Centre,Institute for Remote Snsing Applications. Italy:Ispra,1995

[15] Fourty Th,Baret F. On spectral estimates of fresh leaf biochemistry. International Journal of Remote Sensing,1998,19 (7):1283-1297

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