李蕊,李国清,卢小平,张向军,于海坤

• 1:河南理工大学自然资源部矿山时空信息与生态修复重点实验室
• 2:河南省遥感测绘院

摘要(Abstract)：

针对现有归一化植被指数(NDVI)阈值方法提取冬小麦种植面积受主观因素影响大，建立的模型不具有普适性等问题，该文以Sentinel-2为数据源，冬小麦种植大县——河南省开封市祥符区(原开封县)为实验区，对基于NDVI时间序列建立的冬小麦识别方法进行改进，使用迭代处理方法改进标准时间序列曲线的确定，提取NDVI时间序列的距离、方向特征以及物候期内最大NDVI值作为识别特征参量，运用数学统计方法确定分类模型阈值，据此构建一种改进的时间序列下冬小麦遥感识别矢量模型。结果表明，该方法对冬小麦遥感识别效果较好，提取的冬小麦种植面积Hellden精度达到92.23%。

关键词(KeyWords)： Sentinel-2;归一化植被指数时间序列;迭代处理;改进标准时间序列曲线;冬小麦识别

Abstract:

Keywords:

基金项目(Foundation): 灾害环境下快速应急定位组网技术项目（2016YFC0803103）;; 河南省自然资源厅2021年度自然资源科研项目

作者(Author): 李蕊,李国清,卢小平,张向军,于海坤

DOI: 10.16251/j.cnki.1009-2307.2022.04.010

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