Geo-position technologies in city use research: accuracy evaluation in the context of university students mobility

In the last years the broad potentiality and utility that geo tracking systems can offer have been explored in research fields not only related to geography, but medicine, leisure and tourism as well. Although this technology has been employed in mobility and transportation system analysis, there is still a lack of studies in the urbanism field. This research seeks to evaluate the accuracy of geo-positioning technology tools in the analysis of peoples’ movement and flows in the city. Therefore, we have performed an experiment using Campus Mobility, an open source application for Android smartphones developed by the Mobility, Transport and Territory Studies Group (GEMOTT) of the Autonomous University of Barcelona (UAB) based on SpaceMapper by John Palmer. While activated, the app tracks and records automatically spatiotemporal data from volunteers’ smartphones every two minutes through the GPS. By the end of the experiment, a large dataset with more than 47.000 entries has been generated, including geographical position (latitude and longitude), date and time (timestamp) as well as an anonymous user ID. Additionally to the experiment, a survey has been applied to volunteers in order to contrast and complement results from automatically gathered data and users answers. From the obtained dataset, we have investigated users’ paths, movement and meeting points analytically and graphically, aiming to recognize patterns in volunteers’ displacement and to detect possible anomalous data. For the graphic analyses we have created data visualizations in addition to dynamic maps that have been developed using ArcGIS and CartoDB tools. Both outcomes were combined in order to gain a deep understanding on the shortcomings and possibilities that geo-positioning technology tools offer to urban investigation field. Finally we conclude that, despite minor errors, geo-position technology tools provide new great possibilities for city flows and mobility studies, being able to gather automatically a very large amount of detailed data that would be impossible to collect without an automated process. GPS tracking can be considered a powerful resource for urban studies, although those tools are not entirely accurate if applied to a very small scale analysis

Explora : interactive querying of multidimensional data in the context of smart cities

Citizen engagement is one of the key factors for smart city initiatives to remain sustainable over time. This in turn entails providing citizens and other relevant stakeholders with the latest data and tools that enable them to derive insights that add value to their day-to-day life. The massive volume of data being constantly produced in these smart city environments makes satisfying this requirement particularly challenging. This paper introduces Explora, a generic framework for serving interactive low-latency requests, typical of visual exploratory applications on spatiotemporal data, which leverages the stream processing for deriving-on ingestion time-synopsis data structures that concisely capture the spatial and temporal trends and dynamics of the sensed variables and serve as compacted data sets to provide fast (approximate) answers to visual queries on smart city data. The experimental evaluation conducted on proof-of-concept implementations of Explora, based on traditional database and distributed data processing setups, accounts for a decrease of up to 2 orders of magnitude in query latency compared to queries running on the base raw data at the expense of less than 10% query accuracy and 30% data footprint. The implementation of the framework on real smart city data along with the obtained experimental results prove the feasibility of the proposed approach

Spatio-temporal visualisation and data exploration of traditional ecological knowledge/indigenous knowledge

Traditional Ecological Knowledge (TEK) has been at the centre of mapping efforts for decades. Indigenous knowledge (IK) is a critical subset of TEK, and Indigenous peoples utilize a wide variety of techniques for keeping track of time. Although techniques for mapping and visualizing the temporal aspects of TEK/IK have been utilized, the spatio-temporal dimensions of TEK are not well explored visually outside of seasonal data and narrative approaches. Existing spatio-temporal models can add new visualization approaches for TEK but are limited by ontological constraints regarding time, particularly the poor support for multi-cyclical data and localized timing. For TEK to be well represented, flexible systems are needed for modelling and mapping time that correspond well with traditional conceptions of time being supported. These approaches can take cues from previous spatio-temporal visualization work in the GIS community, and from temporal depictions extant in existing cultural traditions