基于ISODATA的冬小麦籽粒蛋白质含量遥感分级监测

Classified Monitoring of Grain Protein Contents of Winter Wheat by TM Image Based on ISODATA

对冬小麦籽粒蛋白质含量进行遥感分级监测预报,有利于农业管理部门大面积获取田间长势信息,便于及时制定有效的栽培管理措施,实现调优品质的目的。以江苏省姜堰市为例,进行基于TM卫星遥感技术的冬小麦蛋白质含量的监测研究。在利用GPS实地采样调查和建立解译标志的基础上,采用优化的ISODATA分类方法,结合人机交互式判读解译等操作,将样点的信息数据贯穿于整个分类过程;利用分类提取的冬小麦面积数据,反演叶面积指数、生物量和植株氮素含量信息,结合基于光谱参数与氮素积累的冬小麦籽粒蛋白质含量预测模型,对整个区域的冬小麦籽粒蛋白含量进行监测预报,对叠加样点实测数据进行了检验。结果表明,冬小麦面积信息解译精度在95%以上,籽粒蛋白质含量预报精度达到90%以上,最终制作了区域的冬小麦籽粒蛋白质含量分级监测专题图。

Estimating the grain protein contents in winter wheat in different growth stages by remote sensing technology may help farmers to acquire the growth information of winter wheat timely so as to achieve good quality. The protein contents in winter wheat was monitored using the remote sensing technology based on land-sat TM image in Jiangyan city, Jiangsu Province. By November 2008, 20 test sites were distributed almost all over the county. The geographical position and some other information of these samples such as areas＇ shapes had been measured by the handhold GPS machines. The GPS data and the interpretation mark were used to correct TM image, verify the unsupervised classification, assist human-computer interactive interpretation, and other operations. The test data participated the whole classification process based on ISODATA. The leaf area index （LAI） and the plant nitrogen accumulation got from the normalized difference vegetation index （NDVI） inversion and the biomass from the ratio regetation index （RV1） inversion at anthesis, combined with the protein content estimation model of winter wheat grain were applied to the winter wheat grain protein eontent monitoring, and made a winter wheat quality produetion grading thematie map. The accuracy of interpreted information for winter wheat area was more than 95% , and the estimation accuraey of the grain protein contents was above 90%.