José Ignacio Huertas
ABSTRACT
Traditionally, urban traveling patterns have been obtained through origin-destination surveys. This method presents drawbacks such as high costs, limited representativeness of the surveyed population, and low spatial and temporal resolution of the results obtained. This study proposes deploying historical data on mobile device geolocalization to depict population displacement patterns with high spatial and temporal resolution levels. As an illustrative example, the traveling patterns were derived for a megacity in Latin America (the metropolitan area of Monterrey, Mexico) with a database of 0.7 million users being monitored during three months. The solutions formulated to tackle the challenges posed by this proposed method are described, as well as the use of the information gathered to obtain dynamic origin-destination matrices, quantify the average number of daily trips and kilometers traveled per inhabitant, attain population density per hour, and to identify the destinations attractor of most trips. We also suggest using this information to assess the impact of massive events such as concerts and sports gatherings on city mobility and air pollution.
- J. Wolf, "Applications of New Technologies in Travel Surveys', in Travel Survey Methods, P. Stopher and C. Stecher, Eds., Emerald Group Publishing Limited, 2006, pp. 531--544. doi: 10.1108/9780080464015-029.Google Scholar
Cross Ref
- K. Currans and K. Clifton, "Using household travel surveys to adjust ITE trip generation rates', Journal of Transport and Land Use, vol. 8, p. 85, Apr. 2015, doi: 10.5198/jtlu.2015.470.Google ScholarCross Ref
- M. D. Meyer and Institute of Transportation Engineers, Eds., Transportation planning handbook, Fourth edition. [Hoboken, New Jersey}: Wiley, 2016.Google Scholar
- C. Inbakaran and A. Kroen, "Travel Surveys -- Review of international survey methods', ATRF 2011 - 34th Australasian Transport Research Forum, Jan. 2014.Google Scholar
- A. N. Larijani, A.-M. Olteanu-Raimond, J. Perret, M. Brédif, and C. Ziemlicki, "Investigating the Mobile Phone Data to Estimate the Origin Destination Flow and Analysis; Case Study: Paris Region', Transportation Research Procedia, vol. 6, pp. 64--78, Jan. 2015, doi: 10.1016/j.trpro.2015.03.006.Google ScholarCross Ref
- "Rezago Social a Nivel Zonas Urbanas | CONEVAL'. Accessed: Aug. 30, 2023. [Online]. Available: https://www.coneval.org.mx/Medicion/IRS/Paginas/Rezago_social_AGEB_2010.aspxGoogle Scholar
- L. Pappalardo, F. Simini, G. Barlacchi, and R. Pellungrini, "Scikit-mobility: a Python library for the analysis, generation and risk assessment of mobility data'. arXiv, Jun. 04, 2021. doi: 10.48550/arXiv.1907.07062.Google ScholarCross Ref
- "Scikit-mobility - scikit-mobility documentation'. Accessed: Jun. 10, 2023. [Online]. Available: https://scikit-mobility.github.io/scikit-mobility/Google Scholar
- W.-Y. Chiu, G. G. Yen, and T.-K. Juan, "Minimum Manhattan Distance Approach to Multiple Criteria Decision Making in Multiobjective Optimization Problems', IEEE Trans. Evol. Computat., vol. 20, no. 6, pp. 972--985, Dec. 2016, doi: 10.1109/TEVC.2016.2564158.Google ScholarCross Ref
- "Instituto Nacional de Estadística y Geografía (INEGI)'. Accessed: Jun. 10, 2023. [Online]. Available: https://www.inegi.org.mx/Google Scholar
Index Terms
- Profiling Urban Mobility Patterns with High Spatial and Temporal Resolution: A Deep Dive into Cellphone Geo-position Data
Recommendations
Sub-pixel vs. super-pixel-based greenspace mapping along the urban–rural gradient using high spatial resolution Gaofen-2 satellite imagery: a case study of Haidian District, Beijing, China
Greenspace in urban areas is closely related to urban ecosystems, economy, culture, and society. Recently, rapid urban development and expansion are always dominated by a series of human–environment interactions, which can lead to various spatial ...
Spatial urban data system: A cloud-enabled big data infrastructure for social and economic urban analytics
AbstractThe Spatial Urban Data System (SUDS) is a spatial big data infrastructure to support UK-wide analytics of the social and economic aspects of cities and city-regions. It utilises data generated from traditional as well as new and ...
Highlights- A new system for country-wide urban small-area analytics.
- Cloud-enabled spatial ...
High-Resolution Spatial Data Analysis for Monitoring Urban Sprawl in Coastal Zones: A Case Study in Crete Island
Computational Science and Its Applications – ICCSA 2021AbstractUrban sprawl heavily affects coastal areas worldwide, posing threats to the environment and resulting in unsustainable urban growth patterns. This is particularly true in the Mediterranean Region, where coastal and especially insular territories ...
Comments