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吉林蛟河主要树种叶片光谱分类
引用本文:李瑞平,黄侃,黄华国.吉林蛟河主要树种叶片光谱分类[J].东北林业大学学报,2015(3):48-55.
作者姓名:李瑞平  黄侃  黄华国
作者单位:北京林业大学,北京,100083
基金项目:国家“十二五”科技支撑计划项目(2012BAC01B03);国家自然科学基金项目(41171278)
摘    要:运用实验室测量的阔叶红松林的叶片光谱数据,对吉林蛟河实验区的主要树种(红松、白桦、白牛槭、春榆、裂叶榆、蒙古栎、青楷槭、色木槭和紫椴等)的叶片进行分类研究。结果表明:实验室测量叶片光谱数据,针阔树种分类精度达到100%;所有树种分类精度为80%~100%。运用波段响应函数分别模拟多光谱传感器GEOEYE-1、RAPIDEYE和WORDVIEW2的光谱,可以有效区分针阔树种,分类精度为71.6%~100.0%;所有树种分类精度为47.3%~74.0%。

关 键 词:叶片光谱  混交林  树种分类

Leaf Classification of Main Tree Species in Ji aohe of Jilin with Hyperspectral Data
Li Ruiping , Huang Kan , Huang Huaguo.Leaf Classification of Main Tree Species in Ji aohe of Jilin with Hyperspectral Data[J].Journal of Northeast Forestry University,2015(3):48-55.
Authors:Li Ruiping  Huang Kan  Huang Huaguo
Institution:Li Ruiping;Huang Kan;Huang Huaguo;Beijing Forestry University;
Abstract:We studied the leaf classifications with blade hyperspectral data for the main tree species in Jiaohe , Jilin Province. Nine tree species were Piun s koraiensis, Betulaplatyphylla Suk, Acer mandshuricum Maxim., Ulmus japonica, Ulmus lca in-iata (Trautv.) Mayr., Quercus mongolica, Acer tegmentosum Maxim., Acer mono Maxim.and Tilia amurensis Rupr..The classification of needle-leaved and broad-leaved tree species was perfect with an accuracy of 100%.The classification accura-cy among all tree species was in 80.0%-100.0%.We resampled the spectrum into several multispectral sensors ( GEOEYE-1, RAPIDEYE and WORDVIEW2) by using their band response functions , and effectively distinguished coniferous species and deciduous species with the accuracy of 716.%-100.0%.However , the classification accuracy for all species was low with 47.3%-74.0%.
Keywords:Leaf hyper spectral  Mixed forest  Tree species classification
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