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Forecasting Tourist Mobility and Overcrowding thanks to Agent Based Models

By Itzhak Omer and Amit Birenboim, Tel Aviv University

Overcrowding is a main negative externality that is associated with tourism. However, data on street level crowding is usually not available for studying this phenomenon. Using Agent based modelling, we can generate synthetic data of tourist mobility that forecasts street level tourist congestion.

Agent-based models (ABM) enable reference to various individuals’ travel behaviour attributes and to the simultaneous effect of the street network structure and land uses on movement flows. In the Jerusalem case study, ABM is used to represent the different movement patterns of local residents and tourists, and the exposure / interaction between them at the street level. The ABM simulation is based on the following ‘basic’ attributes of agents’ travel behaviour that were found most relevant in previous studies:

 

(i) The attraction/obstruction level of land uses as a destination or as intermediate paths, with distinction between agent types (local residents versus tourists) in this respect;
(ii) Scale/radius for movement and sensitivity to distance: represents the maximal distance available for movement from origin to destination according to destination types and preferences of nearby destinations within this radius;
(iii) Personal status: represents socio-demographic properties, such as age and gender;(iv) Distance type: three types of agents were defined: metric, topological, and angular. Each agent type (local resident and tourist) chooses the relevant shortest path – in terms of metric, topological (the number of turns or direction changes), or angular (cumulative angular change), respectively – between origin-destination pairs.
The ABM was designed with the NetLogo (ver.5.3.1) environment and is associated to geographical layers within ArcGIS software (i.e., street-segment, land uses). Data model is enriched by quantitative data that was collected at the sub urban level such as socio-demographics at the census tract level.
In later stages of the project, the ABM is intended to be used as a decision supporting tool. Using the ABM we will generate forecasted /simulated movement patterns of local residents and tourists according to various scenarios that are related to tourist behavior and tourist-oriented plans or expected trends. Such use of the ABM may help forecasting the implications of changes in the volume and spatial distribution of hotel/Airbnb rooms on local residents-tourists exposure at the street level. The model will also assist to evaluate the implications of urban and infrastructure changes on car usage and walking behavior of various types of agents (e.g., local population, tourists) under different assumptions of technology adoption levels and pricing. Outputs will include, among other things, indices of inclusion and inequality.

Which concepts are linked to the smart city theme? Results based on a bibliometric analysis

by Silvia Blasi and Andrea Ganzaroli, SMARTDEST team – Milan University

This study applies bibliometric analysis for conducting a systematic literature review that enable to map the intellectual structure of the smart city.

We performed a search on the Scopus database, which is one of the most important instruments for collecting systematic information on global scientific literature, especially for mapping an emergent field of research, since it does not include only ISI journals. We preferred to use Scopus instead of WOS (Web of Science) or Google Scholar, because the former includes a more restricted number of journals, with a smaller coverage of the social sciences field, and the latter includes also non-peered review articles and redundant information, making difficult to ensure data quality. Data are analyzed through bibliometrix, an R-tool used to do comprehensive science mapping analysis, which was written by Aria and Cuccurullo (2017). The bibliometrix R-package (http://www.bibliometrix.org) provides a set of tools for quantitative research in bibliometrics and scientometrics.

We identified the articles focused on topics related to the smart cities by performing an advanced search on all the subject categories included in the Scopus database. Following Zheng, Yuan, Zhu, Zhang, & Shao, (2020), we performed a search using as keywords [(“smart* cit*”) OR (“smartcit*”) OR (smart sustainable cit*) OR (“smart communit*”) OR (“intelligent cit*”)] in the title and keywords in Scopus and we considered only English document. Following this procedure, we obtained 1966 documents.

In the picture we can see the co-occurrence networks. Co-occurrence networks are the collective interconnection of terms based on their paired presence within a specified unit of text. Networks are generated by connecting pairs of terms using a set of criteria defining co-occurrence. Looking at figure we can see that the terms are distributed among several clusters. The green, turquoise and orange clusters has formed around the Internet of Things (IoT) and its practical applications in the context of a smart city. This finding confirms our hypothesis that the IoT is to some extent, a “core” term or technological core for a smart city. The term “smart city” itself is more within political and media discourse. From a technological perspective, the IoT is a global infrastructure for the information society that provides the ability for more complex services by connecting (physical and virtual) things to each other based on the existing and developing ICTs. Big data (green cluster) are also a key technology for a smart city. Red cluster contains concepts such as “innovation”, “urbanization”, “infrastructure”, “policy making”. While the green, turquoise and orange clusters tend to spotlight the technological sides of a smart city, the red ones is focused on its organizational and policy issues. The meaning of smartness in the urban or metropolitan context not only indicates utilizing cutting-edge of information and communication technologies (ICTs), but also importantly management and policy concerns. The blue cluster has at its centre the word “smart city” that is linked with “sustainable development”.

For more information you can see the entire report at the following link:

https://www.researchgate.net/publication/344431217_The_spatial_articulation_and_local_effects_of_tourism_and_associated_mobilities

Cycling and walking for safe spaces after lockdown in cities, a “new normality”?

by Alejandro González, GRATET-URV. May 2020

Cities are planning mobility transitions for encouraging cyclists and pedestrians to travel while respecting social distancing.

The capital of Lombardy, the region most hit by Covid-19 in Italy[1] and among the most polluted regions in Europe, plans for a climate-friendly way out of the crisis. This initiative follows other big cities like Paris[2], London[3] or Berlin[4], which are taking advantage of this global crisis in the hope of encouraging cycling and walking to transition to a “new normality” safely. As alternatives to a doctrine shock[5], policies oriented to mobility justice could provide a roadmap for other cities.

Milan[6] has announced that 35km (22 miles) of streets will be transformed over the summer, with a rapid, experimental citywide expansion of cycling and walking space to protect residents as Covid-19 restrictions are lifted. The City Council wants to avoid the increase of pollution in the city during the stage of recovery, in which restrictions to avoid conglomerations in public transport are going to be implemented.

An unjust mobility system may well be related with the pandemic. Intercontinental transport is noted to have directly caused a rapid and global diffusion of the virus, that has subsequently provoked its collapse[7]. But also, the high carbon automobility system may be one of the most important contributors to fatality[8]. Other estimations suggest that more lives were saved due to the reduction in air pollution than those terminated by the virus[9]. Therefore, reducing polluting cars from streets may offer more chances to combat new (corona)virus outbreaks in cities and to make them more resilient.

However, far from being a new normality, Milan was also announced the suspension of the LEZs of the city until 31st of May[10]. Allowing all vehicles to enter, to circulate on public transport preferential lanes and all parking spaces are free for all[11]. Another side of the coin, the coronavirus might have prepared scenarios for shocking and transition. Which one will impose? Will governments take from granted the social de-escalation? Will climate and health prioritise come up on top? A critical analysis is deserved during next months and years to unmask the politics of mobility justice and virus.

[1] BBC (2020 March 22) Coronavirus: Lombardía, la región más golpeada de Italia anuncia medidas más estrictas para frenar el avance del covid-19 Retrieved from https://www.bbc.com/mundo/noticias-internacional-51994635
[2] Carlton, R. (2020 April 22) Paris to Create 650 Kilometers Of Post-Lockdown Cycleways. Forbes. Retrieved from https://www.forbes.com/sites/carltonreid/2020/04/22/paris-to-create-650-kilometers-of-pop-up-corona-cycleways-for-post-lockdown-travel/#6652f1ae54d4
[3] Harrabin, R. (2020 April 20). Coronavirus: Banning cars made easier to aid social distancing. BBC. Retrieved from https://www.bbc.com/news/science-environment-52353942.
[4] Versti, L. (2020 March 27) Neuer temporärer Radweg am Kurfurstendamm. Berliner Morgen Post. Retrieved from https://www.morgenpost.de/bezirke/im-westen-berlins/article228794619/Neuer-temporaerer-Radweg-am-Kurfuerstendamm.html
[5] Moreno, D. (2020 April 1) Naomi Klein: “La gente habla sobre cuándo se volverá a la normalidad, pero la normalidad era la crisis”. El Salto. Retrieved from https://www.elsaltodiario.com/coronavirus/entrevista-naomi-klein-gente-habla-volver-normalidad-crisis-doctrina-shock
[6] Laker, L. (2020 April 21). Milan announces ambitious scheme to reduce car use after lockdown. The Guardian. Retrieved from https://www.theguardian.com/world/2020/apr/21/milan-seeks-to-prevent-post-crisis-return-of-traffic-pollution?fbclid=IwAR0Or0kro67QH_5dkHs4ldazmkvyJtMkQTZOCjdrlqSJa_gvfAio62ICsJA
[7] Pierce, B. (2020) Covid-19: wider economic impact from air transport collapse. IATA. Retrieved from https://www.iata.org/en/iata-repository/publications/economic-reports/covid-19-wider-economic-impact-from-air-transport-collapse/
[8] Carrington, D. (2020 April 20) Air pollution may be ‘key contributor’ to Covid-19 deaths – study. The Guardian. Retrieved from https://www.theguardian.com/environment/2020/apr/20/air-pollution-may-be-key-contributor-to-covid-19-deaths-study
[9] McMahon, J. (2020 Mar 16) Study: Coronavirus Lockdown Likely Saved 77,000 Lives In China Just By Reducing Pollution. Forbes. Retrieved from https://www.forbes.com/sites/jeffmcmahon/2020/03/16/coronavirus-lockdown-may-have-saved-77000-lives-in-china-just-from-pollution-reduction/#2c8cf3c534fe
[10] Interview with Cittadini per l’Aira by email on 08/05/2020 by the author
[11] Idem.