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林业资源管理 ›› 2015, Vol. 0 ›› Issue (4): 45-51.doi: 10.13466/j.cnki.lyzygl.2015.04.009

• 科学研究 • 上一篇    下一篇

若尔盖高寒沼泽植被生物量遥感估算研究

马琼芳1,2, 崔丽娟1, 郝云庆3, 高常军1, 王义飞1, 李伟1   

  1. 1.中国林业科学研究院湿地所,北京 100091;
    2.吉林省林业科学研究院,长春 130033;
    3.四川省林业科学研究院,成都 610081
  • 出版日期:2015-08-28 发布日期:2020-12-01
  • 通讯作者: 崔丽娟。Email:wetlands108@126.com
  • 作者简介:马琼芳(1984-),女,云南人,助理研究员,博士,主要研究领域生态学。
  • 基金资助:
    林业公益性行业科研专项(201204201);吉林省林业厅科技项目(2013-020);林业科技创新平台运行补助项目(2015-LYPT-DW-053)

Satellite Remote Sensing Estimation of Biomass in Ruoergai Alpine Marshes

MA Qiongfang1, 2, CUI Lijuan1, HAO Yunqing3, GAO Changjun1, WANG Yifei1, LI Wei1   

  1. 1.Institute of Wetlands,Chinese Academy of Forestry,Beijing 100091,China;
    2.Academy of Forestry of Jilin Province,Changchun 130033,China;
    3.Academy of Forestry of Sichuan Province,Chengdu 610081,China
  • Online:2015-08-28 Published:2020-12-01

摘要: 采用若尔盖高寒沼泽2011—2012年TM5 遥感数据和同期野外调查获得的32个样地湿地植被生物量数据,分析了遥感影像光谱特征、纹理特征以及地形特征与实测样点地上、地下和总生物量的相关关系并建立多元逐步回归模型,进而计算生物量,结果表明草本沼泽植被生物量与地形因子和纹理特征的相关性不强,与遥感影像及其植被指数等自变量有显著的相关关系。若尔盖高寒沼泽的植被地上、地下、总生物量分别为367.05,3 680.36,4 048.01g/m2。随着地表水分的减少,生物量呈现先增加后减少的趋势。

关键词: 遥感, 生物量, 若尔盖

Abstract: In this paper,the TM5 image of July and August 2011—2012 and 32 sites of aboveground biomass(AGB)and underground biomass(BGB)data of the Rouergai marshes in the same period were used as the data source to establish the estimation models.We examined the relationship between AGB,BGB,total biomass(TB)and spectral information from remote sensing images,topographic factors and texture features.The best estimation models were established.The main results are as followsBoth topographic factors and texture features has no correlation to the herbaceous biomass.There were allometric relationship(p<0.05)between biomass and remote sensing image,vegetation index.The average aboveground biomass(AGB),underguound biomass(BGB)and total biomass(TB)for the Rouergai alpine marshes were 367.05,3680.36 and 4048.01/gm2,respectively.With the reduction of surface water,the biomass increased first and then decreased.

Key words: remote sensing, biomass, Rouergai

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