地理大数据中POI数据质量的评估与提升方法

Evaluation and enhancement methods of POI data quality in the context of geographic big data

地理大数据实现对区域人地系统的精细刻画,为研究人地关系和区域发展等提供新的数据。当前,地理大数据进入了广泛应用,但一直缺乏对其质量的考察及相应的评估方法。兴趣点(POI)数据是地理大数据重要组成部分,对基于位置服务和区域场景理解具有重要作用。本文提出POI类大数据评估与提升方法,基于场地调研、GIS等方法从地物识别完整率、数据冗余率和空间位置准确率3个维度实现质量评估;基于数据生产过程发现和总结数据质量的可能影响因素,证明多源数据融合是提升POI数据质量的有效手段。研究发现,基于API接口获取的高德数据量略高于百度,空间位置准确率相当,冗余率较低;高德侧重识别地物入口,适于可达性等分析;百度侧重发现非标志性地物,适于空间规划等分析;发现、采集和处理阶段是降低数据质量的可能环节,受数据保护机制影响,数据质量与获取量及面积成反比;多源异构地理大数据质量评估、提升与融合是提升数据“涌现价值”、促进多学科交叉融通、解决新时代地理学问题的关键途径之一。

Geographic big data enables a fine-grained depiction of regional human-terrestrial systems and provides new data for the study of human-terrestrial relations and regional development.At present,geographic big data research has entered the stage of widespread application,but the examination of its quality and the corresponding evaluation methods have been lacking to guarantee the widespread and efficient application of the data.POI is an important part of geographic big data and plays an important role in location-based services and an understanding of regional scenarios.This paper proposes a method to assess and enhance POI-type big data,and realize quality evaluation based on site research,GIS and other methods from three dimensions:feature identification completeness,data redundancy rate and spatial location accuracy;discover and summarize possible influencing factors of data quality based on data production process,and prove that multi-source data fusion is an effective means to enhance POI data quality.We found that:the volume of Amap data acquired based on API interface is slightly higher than that of Baidu,the accuracy rate of spatial location is comparable and the redundancy rate is lower;Amap focuses on identifying the entrance of features,which is suitable for analysis such as accessibility;Baidu focuses on discovering non-significant features,which is suitable for analysis such as spatial planning;the discovery,acquisition and processing stages are possible links to reduce data quality,which is influenced by data protection mechanism,and the data quality is inversely proportional to the acquisition volume and area.The quality assessment,enhancement and integration of multi-source heterogeneous geographic data is one of the key ways to enhance the"emergent value"of data,promote trans-and cross-multidisciplinary and solve geographic problems in the new era.