引黄灌区水稻叶面积指数的高光谱估测模型  

Hyperspectral Estimation Model for Predicting LAI of Rice in Ningxia Irrigation Zone

作　　者：秦占飞[1,2] 申健[1] 谢宝妮[1] 严林[1] 常庆瑞[1] QIN Zhanfei SHEN Jian XIE Baoni YAN Lin CHANG Qingrui(College of Natural and Environment, Northwest A＆F University, Yangling 712100, China Institute of Land Resource and Urban and Rural Planning, Hebei GEO University, Shijiazhuang 050031, China)

机构地区：[1]西北农林科技大学资源环境学院,陕西杨凌712100 [2]河北地质大学土地资源与城乡规划学院,河北石家庄050031

出　　处：《武汉大学学报（信息科学版）》2017年第8期1159-1166,共8页Geomatics and Information Science of Wuhan University

基　　金：国家863计划(2013AA102401-2);高等学校博士学科点专项科研基金(20120204110013)~~

摘　　要：水稻叶面积指数(leaf area index,LAI)是评价其长势的重要农学参数,高光谱遥感能够实现叶面积指数的快速无损监测。为了寻找反演水稻LAI的最优植被指数,扩展水稻LAI高光谱估测模型的普适性,选取宁夏引黄灌区水稻为研究对象,通过设置不同氮素处理,借助相关分析、回归分析等方法研究高光谱植被指数与水稻LAI之间的定量关系,并通过确立的最优波段组合,构建4种植被指数与水稻LAI的高光谱反演模型。结果表明,水稻LAI在抽穗末期达到最大值,并随氮素水平的增加而增加;水稻冠层原始光谱反射率在400~722nm和1 990~2 090nm波段与LAI达到极显著负相关水平,在近红外区域760~1 315nm与LAI呈极显著正相关。模型检验结果表明,以比值植被指数RVI(850,750)为变量建立的水稻LAI估测模型最佳,研究结果可为水稻LAI的高光谱估测提供地域参考。Leaf area index（LAI）is one of the important parameters for evaluating rice growth status.Hyperspectral remote sensing is a new technical approach that can be used to acquire LAI information quickly and nondestructively.This study aims to explore the best vegetation index and monitoring model for rice LAI inversion.This study was carried out in Ningxia irrigation zone,where the rice was planted in different fertilizer level.Then the correlation between vegetation index and LAI was analyzed and four inversion models were constructed for estimating LAI by using correlation analysis and regression analysis.The result revealed that the LAI value increased with the increase of nitrogen level,and it reached a maximum value at booting stage and then drops down.The reflectance of rice canopy at the wavebands 400-722nm and 1 990-2 090 nm was very significantly negatively correlated with LAI and that of which at near infrared region（760-1 315nm）was very significantly positively correlated with LAI.The tests with independent dataset suggested that the rice LAI monitoring models with radio vegetation index RVI（850,750）as the variable could give an accurate LAI estimation.These results provided an insight for monitoring the rice LAI in different regions.

关 键 词：水稻 叶面积指数 高光谱 估测模型 引黄灌区 

分 类 号：P237[天文地球—摄影测量与遥感] TP79[天文地球—测绘科学与技术]