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• 研究报告 • 上一篇    下一篇

湿地小叶章叶绿素含量的高光谱遥感估算模型

李凤秀1,2;张柏1;刘殿伟1;王宗明1;宋开山1;靳华安1,2;刘焕军1,2   

  1. 1中国科学院东北地理与农业生态研究所, 长春 130012;2中国
    科学院研究生院, 北京 100039
  • 收稿日期:2007-11-12 修回日期:1900-01-01 出版日期:2008-07-10 发布日期:2008-07-10

Hyperspectral remote sensing estimation models for chlorophyll a concentration ofCalamagrostis angustifolia.

LI Feng-xiu1,2;ZHANG-Bai1;LIU Dian-wei1;WANG Zong-ming1; SONG Kai-shan1;JIN Hua-an1,2;LIU Huan-jun1,2   

  1. 1Northeast Institute of Geography and Agricultural Ecology, Chinese Aca
    demy of Sciences, Changchun 130012, China; 2Graduate University of Chinese Academy of Sciences, Beijing 100039, China
  • Received:2007-11-12 Revised:1900-01-01 Online:2008-07-10 Published:2008-07-10

摘要: 通过实测不同覆盖度和水深状况下小叶章(Calamagroestis angustifolia)的冠层高光谱反射率与叶绿素a(Chl-a)浓度,采用高光谱可见光近红外波段及其微分光谱波段(350~1050 nm)逐波段构建FNDVI、FRVI、FDVI、FDNDVI、FDRVI和FDDVI植被指数,分别找出与Chl-a具有最佳相关性波段组合的植被指数,建立小叶章Chl-a含量的最佳估算模型,并对比分析了最佳模型与线性模型的预测精度。结果显示:微分光谱植被指数与Chl-a的最佳预测模型(FDNDVI、FDRVI和FDDVI)比反射率植被指数最佳模型(FNDVI、FRVI和FDVI)的预测精度分别提高了6.86%、4.82%和10.10%;植被指数(FNDVI、FDVI、FDNDVI和FDRVI)与Chl-a含量具有较好的线性关系,而最佳模型比线性模型预测精度仅仅提高了0.60%、1.40%、1.02%和0.93%,可以用简单的线性模型反演湿地小叶章的Chl-a含量。

关键词: 重庆, 生态足迹, 生态承载量

Abstract: The canopy reflectance and Chl-a concentration of Calamagrostis angustifolia grown under the conditions of different vegetation coverage and water depth were measured with ASD spectroradiometer. Hyperspectral visible light-near infrared bands and their derivative spectral bands (350-1 050 mm) were adopted to construct the vegetation indices FNDVI, FRVI, FDVI, FDNDVI, FDRVI and FDDVI one by one, search after the best band for each vegetation index which had the best correlation with Chl-a, and establish the optimum estimation models for the Chl-a concentration of C. angustifolia. The comparison of the prediction precision between optimum estimation models and linear models showed that the prediction precision of the best forecasting models (FDNDVI, FDRVI and FDDVI) for derivative spectral vegetation indices and Chl-a was respectively 6.86%, 4.82% and 10.10% higher than that of the optimum reflectance vegetation index models (FNDVI, FRVI and FDVI). Vegetation indices (FNDVI, FDVI, FDNDVI, FDRVI) had a great linear relationship with Chl-a, and the prediction precision of the optimum estimation models were only increased by 0.60%, 1.40%, 1.02% and 0.93%, respectively than the linear models, suggesting that the simple linear models could be used to retrieve the Chl-a concentration of C. angustifolia in wetland.

Key words: Chongqing, Ecological footprint, Available ecological capacity