Quality assessment of volunteered geographic information for outdoor activities: an analysis of OpenStreetMap data for names of peaks in Japan

Quality assessment of volunteered geographic information for outdoor activities: an analysis of OpenStreetMap data for names of peaks in Japan
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DOI:
10.1080/10095020.2022.2085188
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发表时间:
2022-07
影响因子:
6
通讯作者:
Jun Yamashita;Toshikazu Seto;N. Iwasaki;Yuichiro Nishimura
Jun Yamashita;Toshikazu Seto;N. Iwasaki;Yuichiro Nishimura
中科院分区:
地球科学2区
文献类型:
--
作者:
Jun Yamashita;Toshikazu Seto;N. Iwasaki;Yuichiro Nishimura

文献摘要

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摘要近年来,随着户外活动在世界范围内的普及,包括在日本,户外活动的地理研究也在增加。数字地理信息(VGI)是组织户外活动的关键工具,因为它提供了一种确定位置信息和地名的方法。为了评估VGI的质量,土地测量机构和其他VGI生成的地理空间数据通常用作参考数据。然而,由于这些参考数据可能不可用,因此需要其他方法来确保VGI的质量。在本研究中,我们通过一个实证案例研究,研究了基于VGI的内在特征的五个信任指标。我们使用从日本OpenStreetMap中提取的山名作为数据,因为附近几乎没有其他VGI。因此,我们分离出三个信任指标,即版本,用户和标签更正,以检查VGI的主题准确性,因为这些是唯一具有统计意义的指标。然而,我们发现,主题准确率的预测率很低。为了提高主题的准确性,本研究建议使用最准确的版本,应用正确的标签,并考虑VGI贡献者的动机和特点。
ABSTRACT Geographical studies of outdoor activities have increased in recent years with the rise in popularity of these activities worldwide, including in Japan. Volunteered geographic information (VGI) is a key tool for organizing outdoor activities as it offers a means to determine the locational information and names of places. To evaluate the quality of VGI, geospatial data generated by land survey agencies and other VGI are often utilized as reference data. However, since these reference data may not be available, other methods are necessary to assure the quality of VGI. In this study, we examined five trust indicators based on the inherent characteristics of VGI through an empirical case study. We used mountain names extracted from OpenStreetMap in Japan as data because there were almost no other VGI in the vicinity. As a result, we isolated three trust indicators, namely versions, users, and tag corrections, to examine the thematic accuracy of VGI because these were the only statistically significant indicators. However, we found that the prediction rate of thematic accuracy was very low. To improve thematic accuracy, this study recommends using the most accurate versions, applying correctly given tags, and considering the motivations and characteristics of the VGI contributors.