文章基本信息

标题：MatchingLand, geospatial data testbed for the assessment of matching methods
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作者：Emerson M. A. Xavier ; Francisco J. Ariza-López ; Manuel A. Ureña-Cámara 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2017
卷号：4
DOI：10.1038/sdata.2017.180
语种：English
出版社：Nature Publishing Group
摘要：This article presents datasets prepared with the aim of helping the evaluation of geospatial matching methods for vector data. These datasets were built up from mapping data produced by official Spanish mapping agencies. The testbed supplied encompasses the three geometry types: point, line and area. Initial datasets were submitted to geometric transformations in order to generate synthetic datasets. These transformations represent factors that might influence the performance of geospatial matching methods, like the morphology of linear or areal features, systematic transformations, and random disturbance over initial data. We call our 11 GiB benchmark data ‘MatchingLand’ and we hope it can be useful for the geographic information science research community.