基于NDVI-Ts特征空间的冬小麦水分诊断与长势监测  

Water deficit diagnosis and growing condition monitoring of winter wheat based on NDVI-Ts feature space

作　　者：刘云[1] 孙丹峰[2] 宇振荣[2] 侯世全[2] 

机构地区：[1]北京农学院园林系,北京102206 [2]中国农业大学资源与环境学院,北京100193

出　　处：《农业工程学报》2008年第5期147-151,共5页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金(30270776)和(40501029)

摘　　要：综合利用NOAA气象卫星4个波段的信息,来证实NDVI-Ts特征空间是否可用于作物的水分亏缺诊断以及监测作物长势。该文在NOAA17/AVHRR数据基础上,利用其1和2通道的数据计算了NDVI,利用4和5通道数据采用优选出的UL92裂窗算法反演了Ts,以邯郸地区为例计算了其植被供水指数(NDVI/Ts)并用NDVI-Ts二维特征空间分析该区冬小麦长势的情况。结果表明:NDVI/Ts基本能诊断邯郸地区冬小麦关键生育期(拔节和灌浆)的水分亏缺状况;NDVI-Ts二维特征空间表证了在各生育期冬小麦地的NDVI和Ts呈反比线性关系,而裸地二者没有相关性,证明了NDVI-Ts特征空间确实是研究作物水分亏缺和长势监测实用的理论方法。Information of 4 bands of NOAA meteorological satellite was utilized synthetically to confirm whether the NDVI-Ts feature space can be used to diagnose water deficit and monitor the crop growth. Based on the data foundation of NOAA17/AVHRR, NDVI was calculated using its 1 and 2 channel data, and Ts was inversed using UL92 split-window algorithm optimized by its 4 and 5 channel data. Took Handan area for case, water supply vegetation index （NDVI/Ts） was calculated, and NDVI-Ts two-dimensional feature space was used to analyze the growing situation of winter wheat. The results show that NDVI/Ts can be used to diagnose water deficit of winter wheat during key growth stages in Handan area. NDVI-Ts feature space indicates a linear and inverse relation between NDVI and Ts for winter wheat land, no relativity for bare land, which can prove that NDVI-Ts feature space is a practical theoretical method to diagnosis water deficit and monitor crop growth.

关 键 词：TS NDVI 水分亏缺诊断 长势监测 冬小麦 

分 类 号：S127[农业科学—农业基础科学] TP79[自动化与计算机技术—检测技术与自动化装置]