朱佳明;郭云开;刘海洋;蒋明;

• 1:长沙理工大学交通运输工程学院/测绘遥感应用技术研究所

摘要(Abstract)：

针对传统PRO4SAIL+查找表方法反演叶面积指数存在查找表过于庞大,反演速度较慢等问题,该文提出一种基于PRO4SAIL与局部加权多元回归组合模型反演叶面积指数的方法。通过利用卫星传感器光谱响应函数实现了实测端元高光谱向像元多光谱的转化,解决了测量尺度不同导致的反射率差异问题;选取两种叶面积指数植被指数MTVI1和MCARI1作为反演因子,同时只选用40组PRO4SAIL模型模拟数据建立训练组,解决查找表数据量过大的问题;将局部加权多元回归的权重因子距离公式按照反演因子个数从一维空间扩展至多维空间,更符合实际应用。该组合模型的预测决定系数为0.727 1,平均相对误差为11.09%,传统查找表的预测决定系数为0.693 2,平均相对误差为13.63%。实验结果表明:组合模型具有较好的预测能力,反演得到的叶面积指数含量精度较高,可为更好地监测路域植被生态环境提供技术支撑。

关键词(KeyWords)： PRO4SAIL模型;局部加权多元回归;叶面积指数;光谱响应函数;路域植被

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(41471421,41671498)

作者(Authors): 朱佳明;郭云开;刘海洋;蒋明;

DOI: 10.16251/j.cnki.1009-2307.2019.01.012

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