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基于冠层反射光谱的棉花干物质积累量估测
引用本文:朱艳,吴华兵,田永超,姚霞,周治国,曹卫星.基于冠层反射光谱的棉花干物质积累量估测[J].应用生态学报,2008,19(1):105-109.
作者姓名:朱艳  吴华兵  田永超  姚霞  周治国  曹卫星
作者单位:南京农业大学江苏省信息农业高技术研究重点实验室,南京,210095
基金项目:国家自然科学基金 , 江苏省自然科学基金
摘    要:通过分析不同施氮水平下棉花地上部干物质积累量与冠层光谱反射率及其衍生的比值植被指数(RVI)、归一化植被指数(NDVI)及差值植被指数(DVI)之间的关系,确立了棉花地上部干物质积累量的敏感波段及预测模型.结果表明:两个可见光波段(560和710 nm)和5个近红外波段(810、870、950、1 100和1 220 nm)组成的植被指数与棉花地上部干物质积累量的相关性较好,其中RVI(1 100, 560)的相关性最好.通过逐步回归分析确立的棉花地上部干物质积累量的预测模型为:地上部干物质积累量(g·m-2)=66.274×RVI(1 100, 560)-148.84.说明通过遥感手段估测棉花地上部干物质积累量是可行的.

关 键 词:水稻  CO2浓度增加  含N率  N素生产效率  
文章编号:1001-9332(2008)01-0105-05
收稿时间:2006-12-20
修稿时间:2007-11-07

Estimation of dry matter accumulation in above-ground part of cotton by means of canopy reflectance spectra
ZHU Yan,WU Hua-bing,TIAN Yong-chao,YAO Xia,ZHOU Zhi-guo,CAO Wei-xing.Estimation of dry matter accumulation in above-ground part of cotton by means of canopy reflectance spectra[J].Chinese Journal of Applied Ecology,2008,19(1):105-109.
Authors:ZHU Yan  WU Hua-bing  TIAN Yong-chao  YAO Xia  ZHOU Zhi-guo  CAO Wei-xing
Institution:Hi-tech Key Laboratory of Information Agriculture of Jiangsu Province, Nanjing Agricultural University, Nanjing 210095, China. yanzhu@njau.edu.cn
Abstract: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.
Keywords:cotton  dry matter accumulation  canopy reflectance  vegetation index  estimation model  
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