基于地—空遥感耦合的冬小麦叶片氮积累量估算  

Estimation of winter wheat leaf nitrogen accumulation based on coupling ground-and space-remotely sensed information

作　　者：王来刚[1,2] 田永超[1] 李文龙[1] 朱艳[1] 曹卫星[1] 

机构地区：[1]国家信息农业工程技术中心/江苏省信息农业高技术研究重点实验室/南京农业大学,南京210095 [2]河南省农业科学院农业经济与信息研究中心,郑州410002

出　　处：《应用生态学报》2012年第1期73-80,共8页Chinese Journal of Applied Ecology

基　　金：国家自然科学基金项目(30871448);江苏省自然科学基金项目(BK2008330);江苏省科技支撑计划项目(BE2010395);教育部新世纪优秀人才支持计划项目(NCET-08-0797)资助

摘　　要：利用不同冬小麦生态区同步的SPOT-5多光谱遥感影像、地面光谱数据和植株取样数据,提出一种基于波谱响应函数拟合和混合像元分解的纯净像元光谱提取方法,并对比分析了纯净像元光谱、模拟像元光谱和实测像元光谱与冬小麦叶片氮积累量(LNA)的定量关系.结果表明:模拟像元光谱对叶片氮积累量的反演效果较好,纯净像元光谱反演效果次之,实测像元光谱最差;但基于模拟像元光谱的LNA监测模型不能直接外推至空间尺度.模型检验结果表明,基于纯净像元光谱的LNA监测模型在2个小麦生态区均具有较好的精度和稳定性,该方法综合利用了地-空遥感的优点,可以推广应用到其他不同空间分辨率和光谱分辨率的遥感数据,从而为区域性冬小麦氮素营养状况的遥感监测提供技术依据.By coupling the SPOT-5 multi-spectral RS images, ground-spectrum, and field measured data of different winter wheat ecological zones, a pure pixel spectrum extraction method was developed based on spectral response function and pixel unmixed, and the quantitative relationships between leaf nitrogen accumulation （LNA） and simulated, measured, and pure pixel spectra were analyzed. The estimation accuracy for LNA was in the sequence of simulated pixel spectra pure pixel spectra measured pixel spectra. However, the LNA monitoring model based on simulated pixel spectra couldn’t be extrapolated directly to spatial level. The results of model verification also indicated that the monitoring model based on pure pixel spectra performed well in two different wheat ecological zones. Therefore, the pure pixel spectrum extraction method could be applied to other varied and remotely sensed data with different spatial and spectral resolutions by making use of the merits of ground- and space- remote sensing simultaneously, which provided a technological basis for estimating winter wheat nitrogen status in regional scale.

关 键 词：冬小麦 叶片氮积累量 波谱响应函数 混合像元分解 纯净像元光谱 

分 类 号：S512.11[农业科学—作物学]