Exploratory analysis of OpenStreetMap for land use classification

J. Estima, M. Painho
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引用次数: 79

Abstract

In the last years, volunteers have been contributing massively to what we know nowadays as Volunteered Geographic Information. This huge amount of data might be hiding a vast geographical richness and therefore research needs to be conducted to explore their potential and use it in the solution of real world problems. In this study we conduct an exploratory analysis of data from the OpenStreetMap initiative. Using the Corine Land Cover database as reference and continental Portugal as the study area, we establish a possible correspondence between both classification nomenclatures, evaluate the quality of OpenStreetMap polygon features classification against Corine Land Cover classes from level 1 nomenclature, and analyze the spatial distribution of OpenStreetMap classes over continental Portugal. A global classification accuracy around 76% and interesting coverage areas' values are remarkable and promising results that encourages us for future research on this topic.
OpenStreetMap用于土地利用分类的探索性分析
在过去的几年里,志愿者们为我们今天所知的“志愿地理信息”做出了巨大贡献。这些庞大的数据可能隐藏着巨大的地理丰富性,因此需要进行研究以探索它们的潜力,并将其用于解决现实世界的问题。在这项研究中,我们对来自OpenStreetMap计划的数据进行了探索性分析。以Corine土地覆盖数据库为参考,以葡萄牙大陆为研究区域,建立了两种分类命名法之间可能的对应关系,并对OpenStreetMap多边形特征分类的质量与Corine土地覆盖分类的一级命名法进行了比较,分析了OpenStreetMap分类在葡萄牙大陆的空间分布。76%左右的全球分类准确率和有趣的覆盖区域值是令人瞩目和有希望的结果,这鼓励了我们对该主题的未来研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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