精准农业技术是基于农田信息在空间和时间上存在的差异而实施的变量管理技术, 本研究以2001年～2002年度在国家精准农业研究示范基地开展的冬小麦变量施肥对比试验为基础, 获取冬小麦拔节期、 灌浆初期及乳熟期的推扫式成像光谱仪(pushbroom hyperspectral imager, PHI)航空高光谱影像数据, 提取反映冬小麦长势光谱参数, 进行变量施肥处理区与常规处理区冬小麦长势空间变异的对比。 研究发现, 变量区与对照区光谱反射率分散度最大的区域主要集中在红边及近红外反射平台的附近, 其中, 乳熟期冬小麦光谱分散度最大, 其次为拔节期和灌浆期。 通过对比不同时相冬小麦长势信息, 发现拔节期变量区作物长势空间变异程度要高于对照区, 经过变量施肥处理后, 灌浆期和乳熟期变量施肥区冬小麦长势空间变异程度低于对照区； 对冬小麦产量的分析发现, 变量区产量的总体空间变异小于对照区, 但变量区总体产量略低于对照区。 研究表明, 利用遥感影像数据, 可以及时获取作物长势的空间变异情况, 为农业管理的生产、 决策及时提供信息。

Precision agriculture technology is defined as an information-and technology-based agriculture management system to identify, analyze and manage crop spatial and temporal variation within fields for optimum profitability, sustainability and protection of the environment. In the present study, push-broom hyperspectral image sensor (PHI) image was used to investigate the spatial variance of winter wheat growth. The variable-rate fertilization contrast experiment was carried out on the National Experimental Station for Precision Agriculture of China during 2001-2002. Three airborne PHI images were acquired during the wheat growth season of 2002. Then contrast analysis about the wheat growth spatial variation was applied to the variable-rate fertilization area and uniformity fertilization area. The results showed that the spectral reflectance standard deviation increased significantly in red edge and short infrared wave band for all images. The wheat milky stage spectral reflectance has the maximum standard deviation in short infrared wave band, then the wheat jointing stage and wheat filling stage. Then six spectrum parameters that sensitive to wheat growth variation were defined and analyzed. The results indicate that parameters spatial variation coefficient for variable-rate experiment area was higher than that of contrast area in jointing stage. However, it decreased after the variable-rate fertilization application. The parameters spatial variation coefficient for variable-rate area was lower than that of contrast area in filling and milking stages. In addition, the yield spatial variation coefficient for variable-rate area was lower than that of contrast area. However, the yield mean value for variable-rate area was lower than that of contrast area. The study showed that the crop growth spatial variance information can be acquired through airborne remote sensing images timely and exactly. Remote sensing technology has provided powerful analytical tools for precision agriculture variable-rate management.Spatial variation