俄罗斯大果沙棘人工林生物量遥感评估与分析

doi:10.7525/j.issn.1673-5102.2015.04.022

植物研究 ›› 2015, Vol. 35 ›› Issue (4): 618-622.doi: 10.7525/j.issn.1673-5102.2015.04.022

俄罗斯大果沙棘人工林生物量遥感评估与分析

王海波；辛颖；赵雨森^*

东北林业大学林学院，哈尔滨　150040

出版日期:2015-07-20 发布日期:2016-03-09
基金资助:

Remote Sensing Evaluation and Analysis of Hippophae rhamnoide Plantation Biomass

WANG Hai-Bo；XIN Ying；ZHAO Yu-Sen^*

College of Forestry,Northeast Forestry University,Harbin　150040

Online:2015-07-20 Published:2016-03-09
Supported by:

摘要/Abstract

摘要： 以2011年的Landsat TM为主要遥感数据，借助于RS和GIS技术完成对俄罗斯大果沙棘人工林生物量进行估侧。结果表明：植被指数和生物量的一元线性回归分析模型中，比值植被指数（RVI）和归一化植被指数（NDVI）与俄罗斯大果沙棘具有较高的相关性，相关系数（R²）分别为0.908 6和0.868 5；基于植被指数和生物量的多元线性回归分析模型中，相关系数（R²）为0.909，经过模型检验，多元回归遥感植被指数模型的精度要高于一元遥感植被指数的精度，但是基于遥感指数模型预测生物量值比理论生物量值偏高。

关键词: 俄罗斯大果沙棘, 人工林生物量, 遥感, 植被指数

Abstract: Weestimated Hippophae rhamnoide plantation biomass using satellite images of Landsat TM(2011)based on RS and GIS. In one-dimensional linear regression analysis models,the NDVI-based and RVI-based simple linear model were the optimal model for estimating biomasswith the coefficient correlation(R²) of 0.908 6 and 0.868 5, respectively. The multiple regression model established by four kinds of VI could be used for estimating forest biomass with the coefficient of determination(R²) of 0.909. Themultivariable linear regression models were better than one-dimensional linear regression analysis models, and the predicted biomass based on regression analysis models was higher than the theoretical biomass.

Key words: Hippophae rhamnoide, plantation biomass, vegetation index(VI), remote sensing, vegetation index

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王海波；辛颖；赵雨森*. 俄罗斯大果沙棘人工林生物量遥感评估与分析[J]. 植物研究, 2015, 35(4): 618-622.

WANG Hai-Bo；XIN Ying；ZHAO Yu-Sen*. Remote Sensing Evaluation and Analysis of Hippophae rhamnoide Plantation Biomass[J]. Bulletin of Botanical Research, 2015, 35(4): 618-622.

俄罗斯大果沙棘人工林生物量遥感评估与分析

Remote Sensing Evaluation and Analysis of Hippophae rhamnoide Plantation Biomass

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