自然资源学报 ›› 2008, Vol. 23 ›› Issue (3): 467-478.doi: 10.11849/zrzyxb.2008.03.013

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基于TM遥感影像的湿地松林生物量研究

马泽清1,2, 刘琪璟1, 徐雯佳1,2, 李轩然1,2, 刘迎春1,2   

  1. 1. 中国科学院地理科学与资源研究所, 北京100101;
    2. 中国科学院研究生院, 北京100049
  • 收稿日期:2006-11-09 修回日期:2007-10-15 出版日期:2008-05-28 发布日期:2008-05-28
  • 通讯作者: 刘琪璟,博士,研究员,主要从事森林生态学及遥感应用研究。E2mai:lliuqijing@gmai.lcom E-mail:lliuqijing@gmai.lcom
  • 作者简介:马泽清(1983-),硕士,主要从事植被生态及遥感的研究。E2mai:lmazq@igsnrr.ac.cn
  • 基金资助:

    国家重点基础研究发展计划(973计划)(2002CB412506)

Study on Biomass of Pinus elliottii Forest in Subtropical China Assisted with Remote Sensing

MA Ze-qing1,2, LIU Qi-jing1, XU Wen-jia1,2, LI Xuan-ran1,2, LIU Ying-chun1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;
    2. Graduate University of Chinese Academy of Sciences,Beijing 100049,China
  • Received:2006-11-09 Revised:2007-10-15 Online:2008-05-28 Published:2008-05-28

摘要: 利用江西千烟洲地区2005年Landsat5TM遥感图像数据和同期野外调查获得的28个样方湿地松(Pinuselliottii)各器官生物量数据,分析了植被指数、影像变换(主成分分析,缨帽变换)结果与森林各器官生物量之间的相关关系,进而建立了光谱-植被指数与生物量多元回归模型。湿地松林各器官与遥感光谱、植被指数拟合相关性大小依次为:叶生物量>枝生物量>地上生物量>树干生物量。通过多元回归模型计算出湿地松林叶生物量平均为573g.m-2,地上生物量平均为6628g.m-2,低于样地调查平均值。单一植被指数与生物量相关性较低,ND-VI并不适用于盖度较大的湿地松林;遥感影像经主成分分析后生物量光谱模型的相关系数略有提高,缨帽变换后反而使模型的相关系数降低。

关键词: 遥感, 植被指数, 森林, 生物量, 千烟洲

Abstract: Based on field survey data,TM imagery acquired in 2005 was applied for organ-specific biomass estimation of Pinus elliottii plantation as well as other forest types in Qianyanzhou of Jiangxi Province,China.A total of 28 plots was investigated and the relationship of biomass with vegetation indices was clarified using image analysis including PCA(Principal Component Analysis) and TASSEL(Tasseled cap transformation).A series of regression models comparing biomass and spectra or vegetation index were established.The sequence of correlation coefficients from high to low was foliage biomass>branch biomass>above-ground biomass>stem biomass.The average above-ground biomass of Pinus elliottii forest as estimated with multiple regression analysis was 6628 g·m-2,with leaf biomass of 573 g·m-2,less than the mean result by field survey.Correlation of biomass with a single vegetation index was quite low,indicating that NDVI alone is not sufficient for estimating biomass of densely closed forest.Results of regression analyses were slightly better using PCA and slightly worse with TASSEL.

Key words: remote sensing, vegetation index, forest, biomass, Qianyanzhou

中图分类号: 

  • Q948