%0 Journal Article
%T Estimation of dry matter accumulation in above-ground part of cotton by means of canopy reflectance spectra<br>基于冠层反射光谱的棉花干物质积累量估测
%A ZHU Yan
%A WU Hua-bing
%A TIAN Yong-chao
%A YAO Xia
%A ZHOU Zhi-guo
%A CAO Wei-xing
%A <br>朱艳
%A 吴华兵
%A 田永超
%A 姚霞
%A 周治国
%A 曹卫星
%J 应用生态学报
%D 2008
%I 
%X Through analyzing the relationships of the dry matter accumulation in above-ground part of cotton with the canopy reflectance of single waveband and all two-band combinations in ratio vegetation index (RVI, R(lamda1)/R(lamda2)), normalized difference vegetation index (NDVI, (R(lamda1)-R(lamda2))/(R(lamda1) + R(lamda2 and differential vegetation index (DVI, R(lamda1)-R(lamda2)), the characteristic spectral wavebands for indicating the dry matter accumulation in above-ground part of cotton were determined, and the corresponding prediction model was established. The results showed that the vegetation indices comprised of visible light (560 and 710 nm) and near infrared light (810, 870, 950, 1100 and 1220 nm) were highly related to the dry matter accumulation in the above-ground part of cotton, and the RVI (1100, 560) was the best spectral index for the estimation. The corresponding prediction model established by stepwise regression method was Y (g x m(-2)) = 66.274 x RVI (1100, 560)-148.84. It could be feasible to estimate the dry matter accumulation in above-ground part of cotton with remote sensing.
%K cotton
%K dry matter accumulation
%K canopy reflectance
%K vegetation index
%K estimation model<br>棉花
%K 干物质积累量
%K 冠层反射率
%K 植被指数
%K 估测模型
%K 冠层反射光谱
%K 棉花
%K 干物质积累量
%K 估测
%K spectra
%K reflectance
%K canopy
%K means
%K cotton
%K dry
%K matter
%K accumulation
%K 手段
%K 遥感
%K 逐步回归分析
%K 相关性
%K 组成
%K 近红外波段
%K 可见光波段
%K 结果
%K 预测模型
%K 敏感波段
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=90BA3D13E7F3BC869AC96FB3DA594E3FE34FBF7B8BC0E591&jid=42FEDDFE54F8BCD9D5FD1926ABDD7722&aid=5B63C31E2E49ED2DBC447647AA4D5BD5&yid=67289AFF6305E306&vid=2A8D03AD8076A2E3&iid=CA4FD0336C81A37A&sid=03F1579EF92A5A32&eid=91C9056D8E8856E0&journal_id=1001-9332&journal_name=应用生态学报&referenced_num=2&reference_num=19