Jiri Horak
ABSTRACT
Abstract. To improve engagement of elderly residents in local community decision making and urban space improvement, two online web mapping applications based on Emotinalmaps.eu were designed. They are intended to collect seniors’ emotions and mark mobility targets. The application utilizes Leaflet library, MySQL database and stores spatial data in GeoJSON. The results of the first campaign in two Czech cities show differences in radii of attractive and repulsive places and paths and provide important information on what the reasons for attractivity/repulsivity are for local elderly. Steep slopes, slippery surfaces, and stairs were recognised as the main barriers. Fourteen categories of mobility targets were marked by respondents. Their spatial distribution was compared against a distribution of all available targets. The testing of M-function confirmed the significant clustering of marked targets for small distances (200-380 m). The distance analysis of targets shows that the selection of targets in an urban close neighbourhood is not driven by the shortest distance and that is why the selection of targets in urban accessibility analysis should not use the distance order of targets, such as the closest facility, but rather a distance threshold or gravity weightings.
- L. Cochrane and J. Corbett, ‘Participatory Mapping‘, in Handbook of Communication for Development and Social Change, Singapore: Springer Singapore, 2018, 1-9, doi: 10.1007/978-981-10-7035-8_6-1Google Scholar
Cross Ref
- S. C. Webber, M. M. Porter, and V. H. Menec, ‘Mobility in Older Adults: A Comprehensive Framework’, The Gerontologist, 50/4, 443–450, 2010, doi: 10.1093/geront/gnq013Google ScholarCross Ref
- J. Bernard, ‘Public transport accessibility: simulation of the usability of public transport in everyday situations‘, Geografie, 127, 2, 145-168, 2022, doi: 10.37040/geografie.2022.002Google ScholarCross Ref
- J. Horak, J. Tesla, D. Fojtik, and V. Vozenilek, ‘Modelling Public Transport Accessibility with Monte Carlo Stochastic Simulations: A Case Study of Ostrava’, Sustainability, 11/24, 2019. doi: 10.3390/su11247098Google ScholarCross Ref
- S. Mavoa, K. Witten, T. McCreanor, and D. O'Sullivan, ‘GIS based destination accessibility via public transit and walking in Auckland, New Zealand’, J. Transp. Geogr., 20/1, 15–22, 2012, doi: 10.1016/j.jtrangeo.2011.10.001.Google ScholarCross Ref
- N.Tilahun and D. Levinson, ‘An Agent-Based Model of Origin Destination Estimation (ABODE)‘, J. of Transport and Land Use, 6/1, 73-88, 2013, doi: 10.5198/jtlu.v1.271Google ScholarCross Ref
- R. G. Donohue, C. M. Sack, and R. E. Roth, “Time Series Proportional Symbol Maps with Leaflet and jQuery”, Cartographic Perspectives, 76, 2014, 43–66, doi: 10.14714/CP76.1248Google ScholarCross Ref
- Jiří Pánek (2019) Mapping citizens’ emotions: participatory planning support system in Olomouc, Czech Republic, J. of Maps, 15/1, 8-12, DOI: 10.1080/17445647.2018.1546624Google ScholarCross Ref
- H. Butler, M. Daly, A. Doyle, S. Gillies, S. Hagen, and T. Schaub, “The GeoJSON Format” (RFC Editor, august 2016), doi: 10.17487/RFC7946.Google ScholarDigital Library
- Marcon, E. and F. Puech. A typology of distance-based measures of spatial concentration. Regional Science and Urban Economics. 62, 56-67, 2017.Google ScholarCross Ref
Index Terms
- Participative Mapping of Elderly Mobility and Distances to Their Favourite Destinations
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