Visual Interactive Exploration of Geo-Located Infrastructure and Facilities in Urban Areas

在许多情况下，公民需要了解城市地区的社区服务和当地基础设施的可用性：搬到新地区的人可能想知道哪个地方符合他们的个人需求；企业家需要了解在某些地区创办新企业的当地潜力。虽然今天的公民可以在网络上访问许多不同的信息源，提供关于城市地区的某种本地化信息，包括地理信息系统，例如谷歌地图，传统网站，例如关于某一地区空气污染的统计网站，或在社交网络(如Facebook)上关于城市某些地区生活质量的讨论。然而，为了从这些信息中获得洞察力，他们需要找到相关的信息来源，单独探索这些来源，然后将结果理智地合并到个人决策中。由于可用数据的数量、分布和异构性，这一过程对最终用户来说是繁琐和耗时的。在URBANEXPLORER中，我们正在研究从不同类型和不同来源检索地理空间相关信息的方法，将这些信息整合到易于解释的新可视化中。超越基于地图的点和区域集群，我们将为服务和基础设施的地理空间可用性的相关方面开发集成和直观可视化的方法，如分布和分布、稀疏性和密度、可达性和连通性。

In many situations, citizens need to understand the availability of community services and local infrastructure in urban areas: Persons moving to a new area may want information about which place meets their individual demands; entrepreneurs need to understand the local potential of founding a new business in some area. While today citizens can access many different sources of information on the Web providing some kind of localized information about urban areas, including geographic information systems, e.g., Google Maps, traditional websites, e.g., statistical websites about air pollution in a certain area, or discussions on social networks (like Facebook) about the quality of live in certain districts of a city. Nevertheless, to gain insights from these information, they need to find the relevant sources of information, explore these sources individually, and then intellectually merge the results into a personal decision. Due to the amount, distribution and heterogeneity of available data, this process is tedious and time consuming for end users. In URBANEXPLORER, we are investigating methods for retrieving geo-spatially related information of different types and from different sources, integrating these into novel visualizations that are easily to interpret. Going beyond map-based points and region clusters, we will develop methods for the integration and intuitive visualization for relevant aspects of the geo-spatial availability of services and infrastructure such as spreading and distribution, sparseness and density, reachability and connectivity.