以用户地理位置为中心的兴趣点标签云  

Points-of-Interest Tag Cloud Centered on the User's Geographic Location

作　　者：成晓强 刘仲宇 吴华意[3] 唐岭军 CHENG Xiaoqiang;LIU Zhongyu;WU Huayi;TANG Lingjun(Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources,Shenzhen 518034,China;Faculty of Resources and Environmental Science,Hubei University,Wuhan 430062,China;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430072,China)

机构地区：[1]自然资源部城市国土资源监测与仿真重点实验室,深圳518034 [2]湖北大学资源环境学院,武汉430062 [3]武汉大学测绘遥感信息工程国家重点实验室,武汉430072

出　　处：《地球信息科学学报》2024年第1期85-98,共14页Journal of Geo-information Science

基　　金：自然资源部城市国土资源监测与仿真重点实验室开放基金资助课题(KF-2021-06-109)。

摘　　要：以基于位置的服务(Location-Based Service,LBS)为研究场景,针对常规地图表达兴趣点的局限,结合标签云的表达优势,设计了一种以用户地理位置为中心、面向兴趣点可视化的“LBS标签云”,并初步实现了一种基于标签径向移位的布局方法。LBS标签云的主要创新是将一个布局中心点引入常规标签云,并根据标签与中心点的空间关系来确定标签的摆放位置。本文设计的布局方法如下:首先,将LBS用户的地理位置作为布局中心点;然后,基于兴趣点名称生成文字标签,并根据兴趣点属性确定标签的字号、字色及其他视觉变量;最后,在极坐标下根据标签与中心点的关系计算标签的初始摆放位置及布局优先级,并按优先级将标签从初始摆放位置依次向外径向移位至与其他标签无压盖的位置。在标签移位过程中,着重考虑角度相邻关系以确保标签距离远近的顺序关系,利用四叉树剖分字形轮廓提高了标签碰撞检测的效率。实验以景点类兴趣点为例,探讨了LBS标签云在3个场景下的可用性及可扩展性。结果表明,相比常规地图,LBS标签云不仅可以展示更多的兴趣点,而且可以有效突出用户关注的信息,如兴趣点的热度、评分及通行时间等。虽然LBS标签云包含一定的距离变形,但多种视觉变量的协同有效缓解了距离变形导致的认知误差。综上,LBS标签云可完整、直观地表达兴趣点的空间分布、多维属性及其与用户位置的关系,是一种新型的、适宜用户高效认知周边环境的可视化形式。Taking Location-Based Services(LBS)as the study context,to address the limitation of visualizing Points of Interest(POI)on conventional maps,a novel tag cloud called“LBS tag cloud”is proposed,and a corresponding generation method based on tag radial displacement is designed in this study.The main innovation of the LBS tag cloud is the incorporation of a layout center into the regular tag cloud and determination of the placement of the tags according to the spatial relationship between the tags and the center.The generation method designed in this paper is outlined as follows:first,the geographical location of the LBS user is used as the layout center;then,the text tag is generated based on the name of the POI,and visual variables such as font size and color of the tag are determined according to the attributes of the POI;and finally,the initial placement position of the tag is calculated according to the relationship between the tag and the center,and the tag is then displaced radially from the initial placement position to a position where there is no overlap with other tags.During the displacement,the order of near and far is ensured based on the angular adjacent relationship.The tag collision detection efficiency is improved by using a quadtree to approximate the glyph outline.Taking the POI of scenic spots as an example,we discuss the usability and scalability of the LBS tag cloud in three scenarios.The results show that compared with conventional maps,the LBS tag cloud can display more POI and effectively highlight the information that users care about,such as the popularity,rating,and travel time of POI.Although the LBS tag cloud contains a certain distance deformation,the synergy of multiple visual variables effectively alleviates the cognitive error caused by the distance deformation.In summary,the LBS tag cloud can completely and intuitively represent the spatial distribution,multi-dimensional attributes of POI,and their relationship with the user's location.It is a new visualization form suitable fo

关 键 词：基于位置的服务 兴趣点 标签云 标签地图 中心型地图 径向移位 可视化 地理信息可视化 

分 类 号：P28[天文地球—地图制图学与地理信息工程] P208[天文地球—测绘科学与技术]