利用MODIS_EVI图像时间序列提取作物种植模式初探

    Preliminary study on cropping pattern mapping using MODIS_EVI image time series

    • 摘要: 作物种植模式对于高效、可控农业管理具有非常重要的意义,通过遥感手段获取种植模式信息是目前亟待解决的难题。以华北平原为试验区,收集了2003年全年每16天合成的MODIS_EVI时间序列图像,从种植模式的MODIS_EVI时间谱分析入手,提取了表征冬小麦及其后茬夏玉米与其他同季生长作物物候差异性特征,分析表明返青期和峰值时期对冬小麦提取贡献最大,而峰值时间和大小以及表征营养生长向生殖生长转化时生物量累积差异的参量(偏斜度)对玉米提取贡献最大。建立了冬小麦和夏玉米的提取模型,各省17个县的抽样表明,冬小麦的总体提取精度为88.38%最后形成了小麦-玉米、小麦-水稻和小麦-其他种植模式的分布图,与作物熟制气候分布图具有较好的一致性。

       

      Abstract: Cropping pattern plays an important role in effective and controllable agricultural management. In this study, the yearly 16-day composite MODIS Enhanced Vegetation Index (EVI) time series covering North China Plain were collected. Phenological features of winter wheat and its succession maize were extracted and analyzed. Re-green stage and peak stage(heading stage) are of great importance for winter wheat extraction, while peak stage (silking stage) and the skew parameter which characterizes the accumulated biomass difference before and after silking stage are the most important for maize extraction. The overall accuracy of wheat mapping is 88.38% when compared with official statistics at county level. The cropping system maps of wheat-maize, wheat-rice, and wheat-other crop are quite consistent with the rotation feasible map regarding climate distribution. The error is caused mostly by the coarse resolution of MODIS and the great spatial variability on a regional scale.

       

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