冬小麦关键物候空间分布遥感监测方法研究

Studies on Remote Sensing Monitoring Method for Spatial Distribution of Winter Wheat Critical Phenology

物候信息对农作物生长的动态监测、田间管理具有重要意义。归一化植被指数(normalized differencevegetation index,NDVI)能够在大范围覆盖区域内准确地反映农作物物候信息。以河北省为研究区域,选用2000至2009年的SPOT/VEGETATION NDVI旬合成产品数据集,尝试结合气象站点的气温,利用Savitzky-Golay(S-G)滤波重构NDVI时序曲线,以动态阈值法监测研究区冬小麦的返青期开始和抽穗期开始,并对监测结果进行了分析。空间分布上,河北省冬小麦物候期总体上呈现由南到北逐渐推迟的空间分布规律,从各具体年份来看,冬小麦遥感监测结果符合实际的物候地面观测结果,并在因异常气候变化物候期发生变化的年份也有较好的反应,结果表明,通过NDVI时序曲线结合气温的方法可以准确监测河北省冬小麦关键物候期。

Crop phenology is of important significance for dynamic monitoring of crop growth and field management. The Normalized Difference Vegetation Index （NDVI） can accurately reflect the crop phenology within a wide range of crop areas. In this paper, SPOT/VEGETATION Maximum Value Composite （MVC） NDVI data in period of 10 days from 2000 to 2009 were used to extract the winter-wheat phenology in Hebei province. The NDVI time series curves are reconstructed by Savitzky-Golay （S-G） filter with air temperature. In the beginning of green-turning and heading stages of winter wheat, the obseived result are analyzed by dynamic threshold method. According to the monitoring results, the winter wheat phenology in Hebei Province shows a special distribution rule of postponing from south to north, and the results of 10 years＇ remote sensing monitoring were consistent with the ground observations of phenology. This indicates that the method proposed in this paper can be used in monitoring winter wheat critical phenology in Hebei province.