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- ItemAdvancing beyond static representations of movement in spatial analysis(Geographical Information Science Research UK, 2020) Holloway, PaulMethods used to generate movement and couple it with the environment are strongly integrated within GIScience. This study explores how systematically altering the conceptualisation of movement, environmental space, and temporal resolution affects the results of habitat selection analyses using both real-world case studies and simulated data. Only segment conceptualisations modelled the expected movement-environment relationship with increasing linear feature resistance. This suggests that spatial statistics employed to investigate movement-environment relationships should advance beyond conceptualising movement as the (relatively) static conceptualisation of vectors and moves and replace these with (more) dynamic aggregations of longer-lasting movement processes such as segments and areal representations.
- ItemTraffic prediction framework for OpenStreetMap using deep learning based complex event processing and open traffic cameras(Schloss Dagstuhl--Leibniz-Zentrum für Informatik GmbH, 2020-09-25) Yaduv, Piyush; Sarkar, Dipto; Salwala, Dhaval; Curry, Edward; Science Foundation IrelandDisplaying near-real-time traffic information is a useful feature of digital navigation maps. However, most commercial providers rely on privacy-compromising measures such as deriving location information from cellphones to estimate traffic. The lack of an open-source traffic estimation method using open data platforms is a bottleneck for building sophisticated navigation services on top of OpenStreetMap (OSM). We propose a deep learning-based Complex Event Processing (CEP) method that relies on publicly available video camera streams for traffic estimation. The proposed framework performs near-real-time object detection and objects property extraction across camera clusters in parallel to derive multiple measures related to traffic with the results visualized on OpenStreetMap. The estimation of object properties (e.g. vehicle speed, count, direction) provides multidimensional data that can be leveraged to create metrics and visualization for congestion beyond commonly used density-based measures. Our approach couples both flow and count measures during interpolation by considering each vehicle as a sample point and their speed as weight. We demonstrate multidimensional traffic metrics (e.g. flow rate, congestion estimation) over OSM by processing 22 traffic cameras from London streets. The system achieves a near-real-time performance of 1.42 seconds median latency and an average F-score of 0.80.
- ItemDigital (Urban) Geography: Student-led research methodology training using smartphone apps(University College Cork, 2019) Holloway, Paul; O'Connor, Ray; Linehan, Denis; Kenna, Therese; Supple, Briony; Delahunty, TomIn the last decade, opportunities have emerged to deploy new digital technologies to research agendas and research-led teaching at third level. For instance, research methods such as surveys and questionnaires are shifting into the digital environment, while at the same time there is increasing evidence to support the view that people who have grown up with technology have acquired distinctive new ways of learning, and that traditional methodologies fail to maximise student engagement (Lafuente 2018). Thompson (2013) suggests that these ‘new learners’ are constantly using technology, multi-tasking in interactive environments, and collaborating online, yet research shows that many students are unaware of the potential of their smartphone to support learning (Woodcock et al, 2012). Despite a widespread interest in mobile devices facilitating teaching and learning in third-level education geography departments (Welsh et al. 2013), many research techniques are still taught using traditional ‘pen-and-paper’ methodologies. The ESRI Collector for ArcGIS is a mobile application (app) that can be used with iOS, Android, and Windows smartphones. Collector for ArcGIS is beginning to emerge as a technology to support spatial thinking in geography at second-level education and third-level education (Pánek and Glass 2018). Here we report on our strategy of integrating mobile technology in GG1015 Applied Geography, a large (250+) class introducing first year BA Arts Geography programme students to a number of techniques that we use in Geography. This module sits between GG1013 Environmental Geography and GG1014 Society and Space in the first-year programme. Both of these modules are a block of 24 1-hour lectures, with multiple choice quizzes (MCQs) and essay-based exams. Subsequently, GG1015 was developed to compliment these modules and introduce different teaching styles that facilitate learning across a range of diversities. Throughout this module, students engage directly in fieldwork, photographic activities, essay writing, presentations, and small group work. As such, this module offers an excellent case study to explore new techniques to engage students in learning, particularly in geographic research.
- ItemSingle use plastics versus consumerism in the case of snack food packaging; evolving societal norms, culture and tipping points(International Sustainable Production and Consumption, 2018-10) Byrne, Edmond P.; Dunphy, Niall P.; Mullally, Gerard; Sage, Colin; Crowley, Shane V.
- ItemThe changing landscape of local and community development in Ireland: policy and practice(The Institute for Social Sciences in the 21st Century (ISS21), University College Cork, 2016-04) Forde, Catherine; O'Byrne, Déirdre; O'Connor, Ray; Ó hAdhmaill, Féilim; Power, Carol; University College Cork