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Using Machine Learning Tools to Classify Sustainability Levels in the Development of Urban Ecosystems

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Using Machine Learning Tools to Classify Sustainability Levels in the Development of Urban Ecosystems

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Molina-Gomez, NI.; Rodriguez-Rojas, K.; Calderón-Rivera, D.; Díaz Arévalo, JL.; López Jiménez, PA. (2020). Using Machine Learning Tools to Classify Sustainability Levels in the Development of Urban Ecosystems. Sustainability. 12(8):1-20. https://doi.org/10.3390/su12083326

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/156565

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Title: Using Machine Learning Tools to Classify Sustainability Levels in the Development of Urban Ecosystems
Author: Molina-Gomez, Nidia Isabel Rodriguez-Rojas, Karen Calderón-Rivera, Dayam Díaz Arévalo, Jose Luis López Jiménez, Petra Amparo
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
Issued date:
Abstract:
[EN] Different studies have been carried out to evaluate the progress made by countries and cities towards achieving sustainability to compare its evolution. However, the micro-territorial level, which encompasses a community ...[+]
Subjects: Urban sustainability , Indicators , Supervised classification , Micro-territories
Copyrigths: Reconocimiento (by)
Source:
Sustainability. (eissn: 2071-1050 )
DOI: 10.3390/su12083326
Publisher:
MDPI AG
Publisher version: https://doi.org/10.3390/su12083326
Type: Artículo

References

Shen, L., Kyllo, J., & Guo, X. (2013). An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability. Sustainability, 5(2), 524-559. doi:10.3390/su5020524

Verma, P., & Raghubanshi, A. S. (2018). Urban sustainability indicators: Challenges and opportunities. Ecological Indicators, 93, 282-291. doi:10.1016/j.ecolind.2018.05.007

Phillis, Y. A., Kouikoglou, V. S., & Verdugo, C. (2017). Urban sustainability assessment and ranking of cities. Computers, Environment and Urban Systems, 64, 254-265. doi:10.1016/j.compenvurbsys.2017.03.002 [+]
Shen, L., Kyllo, J., & Guo, X. (2013). An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability. Sustainability, 5(2), 524-559. doi:10.3390/su5020524

Verma, P., & Raghubanshi, A. S. (2018). Urban sustainability indicators: Challenges and opportunities. Ecological Indicators, 93, 282-291. doi:10.1016/j.ecolind.2018.05.007

Phillis, Y. A., Kouikoglou, V. S., & Verdugo, C. (2017). Urban sustainability assessment and ranking of cities. Computers, Environment and Urban Systems, 64, 254-265. doi:10.1016/j.compenvurbsys.2017.03.002

Gerry Marten, Human Ecology: Basic Concepts for Sustainable Development—Populations and Feedback Systemshttp://gerrymarten.com/ecologia-humana/capitulo02.html

Tanguay, G. A., Rajaonson, J., Lefebvre, J.-F., & Lanoie, P. (2010). Measuring the sustainability of cities: An analysis of the use of local indicators. Ecological Indicators, 10(2), 407-418. doi:10.1016/j.ecolind.2009.07.013

Mapar, M., Jafari, M. J., Mansouri, N., Arjmandi, R., Azizinejad, R., & Ramos, T. B. (2017). Sustainability indicators for municipalities of megacities: Integrating health, safety and environmental performance. Ecological Indicators, 83, 271-291. doi:10.1016/j.ecolind.2017.08.012

Rajaonson, J., & Tanguay, G. A. (2017). A sensitivity analysis to methodological variation in indicator-based urban sustainability assessment: a Quebec case study. Ecological Indicators, 83, 122-131. doi:10.1016/j.ecolind.2017.07.050

Dizdaroglu, D. (2015). Developing micro-level urban ecosystem indicators for sustainability assessment. Environmental Impact Assessment Review, 54, 119-124. doi:10.1016/j.eiar.2015.06.004

Niemeijer, D., & de Groot, R. S. (2008). A conceptual framework for selecting environmental indicator sets. Ecological Indicators, 8(1), 14-25. doi:10.1016/j.ecolind.2006.11.012

Scipioni, A., Mazzi, A., Mason, M., & Manzardo, A. (2009). The Dashboard of Sustainability to measure the local urban sustainable development: The case study of Padua Municipality. Ecological Indicators, 9(2), 364-380. doi:10.1016/j.ecolind.2008.05.002

Hák, T., Janoušková, S., & Moldan, B. (2016). Sustainable Development Goals: A need for relevant indicators. Ecological Indicators, 60, 565-573. doi:10.1016/j.ecolind.2015.08.003

Sotelo, J. A., Tolón, A., & Lastra, X. (2011). Indicadores por y para el desarrollo sostenible, un estudio de caso. Estudios Geográficos, 72(271), 611-654. doi:10.3989/estgeogr.201124

Feleki, E., Vlachokostas, C., & Moussiopoulos, N. (2018). Characterisation of sustainability in urban areas: An analysis of assessment tools with emphasis on European cities. Sustainable Cities and Society, 43, 563-577. doi:10.1016/j.scs.2018.08.025

Ocampo, L., Ebisa, J. A., Ombe, J., & Geen Escoto, M. (2018). Sustainable ecotourism indicators with fuzzy Delphi method – A Philippine perspective. Ecological Indicators, 93, 874-888. doi:10.1016/j.ecolind.2018.05.060

Torres-Delgado, A., & López Palomeque, F. (2018). The ISOST index: A tool for studying sustainable tourism. Journal of Destination Marketing & Management, 8, 281-289. doi:10.1016/j.jdmm.2017.05.005

Cui, X., Fang, C., Liu, H., & Liu, X. (2019). Assessing sustainability of urbanization by a coordinated development index for an Urbanization-Resources-Environment complex system: A case study of Jing-Jin-Ji region, China. Ecological Indicators, 96, 383-391. doi:10.1016/j.ecolind.2018.09.009

Saaty, R. W. (1987). The analytic hierarchy process—what it is and how it is used. Mathematical Modelling, 9(3-5), 161-176. doi:10.1016/0270-0255(87)90473-8

Cortes, C., & Vapnik, V. (1995). Support-vector networks. Machine Learning, 20(3), 273-297. doi:10.1007/bf00994018

R package version 6.0-72https://CRAN.R-project.org/package=caret

nnet: Feed-Forward Neural Networks and Multinomial Log-Linear Modelshttps://cran.r-project.org/web/packages/nnet/index.html

e1071: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wienhttps://cran.r-project.org/web/packages/e1071/index.html

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