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GLAS星载激光雷达和Landsat/ETM+数据的森林生物量估算
引用本文:池泓,黄进良,邱娟,孙国清,付安民.GLAS星载激光雷达和Landsat/ETM+数据的森林生物量估算[J].测绘科学,2018(4):9-16,23.
作者姓名:池泓  黄进良  邱娟  孙国清  付安民
作者单位:中国科学院测量与地球物理研究所,武汉,430077 马里兰大学帕克分校地理系,马里兰州 20742 国家林业局调查规划设计院,北京,100714
基金项目:国家自然科学基金项目(41201371
摘    要:基于大脚印激光雷达数据和野外观测数据,该文提出一种获取脚印点内森林生物量的新思路,并结合陆地卫星数据应用于长白山地区森林地上生物量估算。首先,基于3种森林类型(针叶林、阔叶林和针阔混交林),采用多元逐步回归方法建立激光雷达波形指数与脚印点内实测平均树高的回归模型,估算全部脚印点内的平均树高;然后根据脚印点内样方的野外观测数据(平均树高和平均胸径)以及它们与样方生物量的拟合方程估算没有野外调查数据对应的脚印点的生物量;最后对3种森林类型的脚印点森林生物量在各森林覆盖度条件下进行分层分区统计得到生物量等级图。验证比较遥感估算的生物量与野外调查数据推算的生物量,总体误差在0~30(t·hm~(-2))之间,均方根误差为14.66(t·hm~(-2))。

关 键 词:森林地上生物量  大脚印激光雷达  多元逐步回归  森林覆盖度  陆地卫星  forest  aboveground  biomass  large  footprint  LiDAR  multiple  stepwise  regression  forest  fractional  coverage  Landsat

Estimation of forest aboveground biomass using ICESat/GLAS data and Landsat/ETM+ imagery
CHI Hong,HUANG Jinliang,QIU Juan,SUN Guoqing,FU Anmin.Estimation of forest aboveground biomass using ICESat/GLAS data and Landsat/ETM+ imagery[J].Science of Surveying and Mapping,2018(4):9-16,23.
Authors:CHI Hong  HUANG Jinliang  QIU Juan  SUN Guoqing  FU Anmin
Abstract:Based on field survey data and large footprint LiDAR data,an new approach to estimating forest aboveground biomass(AGB)within footprints was proposed in the paper.This method was applied to estimate forest AGB in Changbai mountain area by using landsat data Firstly,models of three forest types(conifer forests,broadleaf forests and mixed forests)for prediction of mean canopy height at GLAS footprint level were developed from GLAS waveform parameters and mean canopy height of field survey plot through multiple stepwise regression analyses.Then,mean canopy height of each footprint can be estimated.Secondly,equations fitting by field survey data (mean canopy height and diameter at breast height)and biomass derived from wood weight per unit area at sub-footprint level were used to estimate biomass of footprints that were not co-located with field survey plots.Lastly,an AGB map was produced by the processing of footprint biomass stratified statistics with different forest fractional coverage of three forest types.Comparing estimated biomass with field inventory data,the total error was in the range from 0 to 30(t · hm-2),and the root mean square error(RMSE)was 14.66(t · hm-2).
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