Existing urban boundaries are usually defined by government agencies for administrative, economic, and political purposes. However, it is not clear whether the boundaries truly reflect human interactions with urban space in intraand inter-regional activities. Defining urban boundaries that consider socioeconomic relationships and citizen commute patterns is important for many aspects of urban and regional planning. In this paper, we describe a method to delineate urban boundaries based upon human interactions with physical space inferred from social media. Specifically, we depicted the urban boundaries of Great Britain using a mobility network of Twitter user spatial interactions, which was inferred from over 69 million geo-located tweets. We define the nonadministrative anthropographic boundaries in a hierarchical fashion based on different physical movement ranges of users derived from the collective mobility patterns of Twitter users in Great Britain. The results of strongly connected urban regions in the form of communities in the network space yield geographically cohesive, non-overlapping urban areas, which provide a clear delineation of the non-administrative anthropographic urban boundaries of Great Britain. The method was applied to both national (Great Britain) and municipal scales (the London metropolis). While our results corresponded well with the administrative boundaries, many unexpected and interesting boundaries were identified. Importantly, as the depicted urban boundaries exhibited a strong instance of spatial proximity, we employed a gravity model to understand the distance decay effects in shaping the delineated urban boundaries. The model explains how geographical distances found in the mobility patterns affect the interaction intensity among different non-administrative anthropographic urban areas, which provides new insights into human spatial interactions with urban space.
Summary
The interdisciplinary field of cyberGIS (geographic information science and systems (GIS) based on advanced cyberinfrastructure) has a major focus on data‐ and computation‐intensive geospatial analytics. The rapidly growing needs across many application and science domains for such analytics based on disparate geospatial big data poses significant challenges to conventional GIS approaches. This paper describes CyberGIS‐Jupyter, an innovative cyberGIS framework for achieving data‐intensive, reproducible, and scalable geospatial analytics using Jupyter Notebook based on ROGER, the first cyberGIS supercomputer. The framework adapts the Notebook with built‐in cyberGIS capabilities to accelerate gateway application development and sharing while associated data, analytics, and workflow runtime environments are encapsulated into application packages that can be elastically reproduced through cloud‐computing approaches. As a desirable outcome, data‐intensive and scalable geospatial analytics can be efficiently developed and improved and seamlessly reproduced among multidisciplinary users in a novel cyberGIS science gateway environment.
Summary
In recent years, geospatial data have exploded to massive volume and diversity and subsequently cause serious usability issues for researchers in various scientific areas. This paper describes a cyberGIS community data service framework to facilitate geospatial big data access, processing, and sharing based on a hybrid supercomputer architecture. Specifically, the framework aims to enhance the usability of national elevation dataset released by the U.S. Geological Survey in the contiguous United States at the resolution of
1false/3 arc‐second. A community data service, namely TopoLens, is created to demonstrate the workflow integration of national elevation dataset and the associated computation and analysis. Two user‐friendly environments, including a publicly available web application and a private workspace based on the Jupyter notebook, are provided for users to access both precomputed and on‐demand computed high‐resolution elevation data. The system architecture of TopoLens is implemented by exploiting the ROGER supercomputer, the first cyberGIS supercomputer dedicated to geospatial problem‐solving. The usability of TopoLens has been acknowledged in the topographic user community evaluation.
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