Wang Lai-Gang, Tian Yong-Chao, Li Wen-Long, Zhu Yan
National Engineering and Technology Center for Information Agriculture/Jiangsu Province Key Laboratory for Information Agriculture/Nanjing Agricultural University, Nanjing 210095, China.
Ying Yong Sheng Tai Xue Bao. 2012 Jan;23(1):73-80.
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.
通过耦合不同冬小麦生态区的SPOT-5多光谱遥感影像、地面光谱和田间实测数据，基于光谱响应函数和像元分解开发了一种纯像元光谱提取方法，并分析了叶片氮积累量（LNA）与模拟光谱、实测光谱和纯像元光谱之间的定量关系。LNA的估算精度顺序为模拟像元光谱>纯像元光谱>实测像元光谱。然而，基于模拟像元光谱的LNA监测模型不能直接外推到空间尺度。模型验证结果还表明，基于纯像元光谱的监测模型在两个不同的小麦生态区表现良好。因此，纯像元光谱提取方法可以同时利用地面和空间遥感的优点，应用于具有不同空间和光谱分辨率的其他多样遥感数据，为区域尺度冬小麦氮素状况估算提供了技术基础。
