Exploratory analysis of the behavior of volunteer cyclists by spatio-temporal mining patterns in Cuenca, Ecuador

Authors

DOI:

https://doi.org/10.18537/mskn.09.01.13

Keywords:

non-motorized mobility, urban cycling, exploratory analysis, space-time pattern mining, space-time cubes

Abstract

Data mining techniques combined with space-time cubes empower the analysis of multidimensional data. A study area in which these advanced analysis techniques can be applied pre-eminently is urban mobility, where investigation of non-motorized mobility patterns is a main priority for several cities around the world. The presented work aimed to extract spatio-temporal patterns from a human movement database containing volunteer-generated cycling data in Cuenca (Ecuador) with the objective to detect places and times where strategies can be applied that promote urban cycling. The methodology takes advantage of the capabilities of the space-time pattern mining toolbox in ArcGIS. The results demonstrate the viability of the proposed methodology for the characterization of non-motorized mobility patterns and its potential for analyzing other mobility datasets.

 

 

Resumen

El uso de técnicas de minería de datos combinadas con metodologías como los cubos espacio-temporales potencian en gran medida el análisis de bases de datos multidimensionales. Una de las áreas de aplicación más importantes es el estudio de la movilidad no motorizada, la cual constituye una de las prioridades más importantes de la mayor parte ciudades alrededor del mundo. Este estudio busca extraer patrones en una base de datos de movilidad de ciclistas voluntarios en Cuenca (Ecuador) para identificar lugares y momentos relevantes para el diseño y aplicación de estrategias para mejorar la movilidad en bicicleta. La metodología está basada en la caja de herramientas para la minería de patrones espacio-temporales de ArcGIS. Los resultados demuestran la viabilidad de la metodología propuesta para la caracterización de la movilidad no motorizada y su potencial uso en otros conjuntos de datos de movilidad.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

References

Bação, F., Lobo, V., Painho, M. (2005). On the particular characteristics of spatial data and its similarities to secondary data used in data mining. Retrieved from http://www.novaims.unl.pt/docentes/vlobo/Publicacoes/2_13_lobo05_secondary_data.pdf

CCCV. (2016). Calidad de vida en Cuenca. Cuarta encuesta de percepción ciudadana. Retrieved from http://www.cccv.ec/download/20170316_EncuestaCCCV2016(Sitio).pdf

Environmental Systems Research Institute. (2015a). How emerging hot spot analysis works. Retrieved from http://desktop.arcgis.com/en/arcmap/latest/tools/space-time-pattern-mining-toolbox/learnmoreemerging.htm

Environmental Systems Research Institute. (2015b). How local outlier analysis works. Retrieved from http://desktop.arcgis.com/en/arcmap/latest/tools/space-time-pattern-mining-toolbox/learnmorelocaloutlier.htm

Environmental Systems Research Institute. (2016). ArcGIS Desktop 10.5. ESRI. Retrieved from http://www.esri.com/arcgis/about-arcgis

Fayyad, U. U., Piatetsky-Shapiro, G., Smyth, P. (1996). Knowledge discovery and data mining: Towards a unifying framework. Int. Conf. on Knowledge Discovery and Data Mining, pp. 82-88. https://doi.org/10.1.1.27.363

GAD Municipal de Cuenca. (2015). Plan de movilidad y espacios publicos (Tomo I). Cuenca, Ecuador.

Gatalsky, P., Andrienko, N., Andrienko, G. (2004). Interactive analysis of event data using space-time cube. Proc. 8th Int. Conf. on Information Visualisation, IV 2004, 145-152. https://doi.org/10.1109/IV.2004.1320137

Grupo de Investigación LlactaLAB - Ciudades Sustentables. (2015). Científicos en pedales - Científicos a pies. Retrieved from https://llactalab.ucuenca.edu.ec/investigacion/pies-y-pedales/cientificos-en-pedales/

Hägerstraand, T. (1970). What about people in regional science? Papers in Regional Science. https://doi.org/10.1111/j.1435-5597.1970.tb01464.x

Hand, D. J. (1998). General data mining: Statistics and more? The American Statistician, 52(2), 112-118.

INEC. (2010). Información Censal.

Interamerican Development Bank. (2014). Methodological guide: Emerging and sustainable cities initiative (2nd ed.). IDB, 161 p.

Jiang, S., Ferreira, J., González, M. C. (2015). Activity-based human mobility patterns inferred from mobile phone data: A case study of Singapore. IEEE Transactions on Big Data, 1-13. https://doi.org/10.1109/TBDATA.2016.2631141

Molina, L. T., Molina, M. J., Slott, R. S., Kolb, C. E., Gbor, P. K., Meng, F., … Gertler, A. W. (2004). Air quality in selected megacities. Journal of the Air & Waste Management Association, 54, 1-73. https://doi.org/10.1080/10473289.2004.10471015

Openshaw, S. (1999). Geographical data mining: key design issues. 4th International Conference on GeoComputation, Virginia, pp. 1-9.

Orellana, D. (2016). Métodos para el análisis de patrones de movilidad no motorizada. In: Comunidades Urbanas Energéticamente Eficientes (1st ed., pp. 141-147). EDUFES.

Orellana, D., Hermida, C., Osorio, P. (2017). Comprendiendo los patrones de movilidad de ciclistas y peatones: Una síntesis de literatura. Revista Transporte Y Territorio, 16, 168-184.

Pojani, D., Stead, D. (2015). Sustainable urban transport in the developing world: Beyond megacities. Sustainability, 7(6), 7784-7805. https://doi.org/10.3390/su7067784

R Core Team. (2017). R: A language and environment for statistical computing. Vienna, Austria. Retrieved from https://www.r-project.org/

Rew, R., Davis, G. (1990). NetCDF: an interface for scientific data access. IEEE Computer Graphics and Applications, 10(4), 76-82. https://doi.org/10.1109/38.56302

Thierry, B., Chaix, B., Kestens, Y. (2013). Detecting activity locations from raw GPS data: a novel kernel-based algorithm. International Journal of Health Geographics, 12, 14. https://doi.org/10.1186/1476-072X-12-14

Wood, J., Dykes, J., Slingsby, A. (2010). Visualisation of origins, destinations and flows with OD maps. The Cartographic Journal, 47(2), 117-129. https://doi.org/10.1179/000870410X12658023467367

Published

2018-07-12

How to Cite

Abad, L., & Orellana, D. (2018). Exploratory analysis of the behavior of volunteer cyclists by spatio-temporal mining patterns in Cuenca, Ecuador. Maskana, 9(1), 141–151. https://doi.org/10.18537/mskn.09.01.13

Issue

Section

Research articles