research article
oaioai:ir.igsnrr.ac.cn:311030/41819

一种基于概率神经网络的城市用地高分辨率影像信息提取方法

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Publication date
1 January 2016
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Abstract

以国产高分辨率遥感影像为主要数据源,在建立城市用地类型体系的基础上,构建了一套结合面向对象的多尺度分割方法和概率神经网络模型优势的城市用地信息提取方法。对唐山市路南区实例验证表明,本研究提出的城市用地信息提取方法和分类结果能够有效地提取包括城市裸地、建筑用地、水体、绿地、道路等城市用地类型,总体分类精度达86%,kappa系数达0.78

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This paper was published in Institutional Repository of Institute of Geographic Sciences and Natural Resources Research, CAS.

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