Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural
Las tecnologías de investigación social son un conjunto de aplicaciones y modelos formales que posibilitan el abordaje de problemas sociales mediante métodos cuantitativos y cualitativos no necesariamente estadísticos, un gran campo iconológico de explicaciones visuales (Tufte, 1997), perspectivas transdisciplinares de conocimiento y ambientes de trabajo formal libres de disciplina. Este conjunto de aplicaciones presentan diversos retos y alternativas a los modelos mecánicos, estadísticos e interpretativos en estado puro de las ciencias sociales clásicas. El punto de partida de este trabajo enfatiza en la búsqueda de la sostenibilidad ecosistémica en escenarios urbanos y rurales y su investigación interdisciplinar, a propósito del impacto d... Ver más
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Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural Kim, J., Lerch, F. and Simon, H.A. (1995). Internal representation and rule development in object-oriented design. ACM Transactions on Computer-Human Interaction, 2 (4), 357-390. Newell, A. (1990). Unified Theories of Cognition. Cambridge, USA: Harvard University Press. Murcott, A. (Ed.). (1983). The Sociology of Food and Eating: Essays on the Sociological Significance of Food. Aldershot, England: Gower. Moss, S. and Edmonds, B. (2005). Sociology and Simulation: Statistical and Qualitative Cross-Validation. AJS, 110 (4), 1095-1131. LeBaron, B., Arthur, W.B. and Palmer, R. (1999). Time Series Properties of an Artificial Stock Market. Journal of Economic Dynamics and Control, 23, 1487-1516. LeBaron, B. (2002). Short Memory Traders and Their Impact on Group Learning in Financial Markets. Proceedings of the U.S. National Academy of Sciences, 99, 7201-7206. Lansing, J.S. et al. (2017). Adaptive self-organization of Bali’s ancient rice terraces. Proceedings of the National Academy of Sciences, 114 (25), 6504-6509. Lansing, J.S. (2006). Perfect Order: Recognizing Complexity in Bali. New Jersey, USA: Princeton University Press. Klüver, J. (1996). Simulations of Self Organizing Social Systems. En F. Faulbaum and W. Bandilla (Ed.), SoftStat 95. Advances in Statistical Software (pp. 425-432). Stuttgart, Germany: Lucius. John, B.E., Vera, A.H. and Newell, A. (1994). Toward real-time GOMS: A model of expert behavior in a highly interactive task. Behavior and Information Technology, 13, 255-267. Northrop, R.B. and Connor, A.N. (2013). Ecological Sustainability. Understanding Complex Issues. Boca Raton, USA: CRC Press, Taylor & Francis Group. ICSU. (2016). A Draft Framework for Understanding SDG Interactions. Recuperado de https://icsu.org/cms/2017/05/SDG-interactions-working-paper.pdf. Holland, J. (1995). Hidden Order: How Adaptation Builds Complexity. Reading, England: Addison-Wesley. Higgins, A.J. et al. (2010). Applying operations research to agricultural value chain to achieve a balance in efficiency and resilience. Journal of the Operations Research Society, 61, 964-973. Harris, M. (1985). Good to Eat: Riddles of Food and Culture. New York, USA: Simon & Schuster. Gilbert, N., Ahrweiler, P. and Pyka, A. (Ed.). (2014). Simulating Knowledge Dynamics in Innovation Networks. Berlin, Germany: Springer-Verlag. Gilbert, N., Ahrweiler, P. and Pyka, A. (2010). The SKIN (Simulating Knowledge Dynamics in Innovation Networks) model. Mainz, Germany: Johannes Gutenberg University Mainz, University of Hohenheim. Gilbert, N. and Troitzsch, K.G. (2005). Simulation for the Social Scientist. Buckingham, United Kingdom: Open University Press. Frankhauser, P. (2015). From Fractal Urban Pattern Analysis to Fractal Urban Planning Concepts. En M. Helbich, J.J. Arsanjani and M. Leitner (Ed.), Computational Approaches for Urban Environments (pp. 13-48). Geneva, Switzerland: Springer International Publishing. Forrester, J. et al. (2014). Modeling Social-Ecological Problems in Coastal Ecosystems: A Case Study. Complexity, 19, 73-82. Nilsson, M., Griggs, D. and Visbeck, M. (2016). Map the interactions between Sustainable Development Goals. Nature, 534, 320-322. Pascual, M. and Dunne, J.A. (Ed.). (2006). Ecological Networks: Linking Structure to Dynamics in Food Webs. New York, USA: Oxford University Press. Egerton, F.N. (2007). Understanding food chains and food webs, 1700-1970. Bulletin of the Ecological Society of America, 88, 50-69. von Bertalanffy, L. (1976). Teoría general de los sistemas. Fundamentos, desarrollo, aplicaciones. Buenos Aires, Argentina: Fondo de Cultura Económica. Text http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess http://purl.org/coar/version/c_970fb48d4fbd8a85 info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:eu-repo/semantics/article Wilensky, U. and Rand, W. (2015). An Introduction to Agent-Based Modeling. Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, USA: The MIT Press. Wells, J. (2013). Complexity and Sustainability. New York, USA: Routledge. Tufte, E.R. (1997). Visual Explanations. Images and Quantities, Evidence and Narrative. Cheshire/ Connecticut, USA: Graphics Press. Pierce, W.D., Cushman, R.A. and Hood, C.E. (1912). The insect enemies of the cotton boll weevil. U.S. Department of Agriculture, Bureau of Entomology Bulletin, 100, 1-99. Suleiman, R., Troitzsch, K.G. and Gilbert, N. (Ed.). (2000). Tools and Techniques for Social Science Simulation. Heidelberg, Germany: Physica-Verlag. Sibertin-Blanc, C. et al. (2013). SocLab: A Framework for the Modeling, Simulation and Analysis of Power in Social Organizations. Journal of Artificial Societies and Social Simulation, 16 (4). Recuperado de http://jasss.soc.surrey.ac.uk/16/4/8.html. Salingaros, N.A. (2005). Principles of Urban Structure. Amsterdam, Netherlands: Techne Press. Schelling, T. (1978). Micromotives and Macrobehavior. New York, USA: Norton. Reynoso, C. (2013). Etnicidad y redes territoriales: perspectivas de complejidad. En B. Nates (Coord.), La frontera, las fronteras: diálogos transversales en estudios territoriales contemporáneos (pp. 63-90). Riohacha, Colombia: RETEC. Reynoso, C. (2006). Complejidad y caos: una exploración antropológica. Buenos Aires, Argentina: Editorial SB. Reynolds, R. and Kobti, Z. (2003). A Multi-Agent Simulation Using Cultural Algorithms: The Effect of Culture on the Resilience of Social Systems. Recuperado de http://ieeexplore.ieee.org/document/1299917/?reload=true. Reynolds, G.R. (1994). An Introduction to Cultural Algorithms. Recuperado de http://ai.cs.wayne.edu/ai/availablePapersOnLine/IntroToCA.pdf. Reeves, C.R. (1993). Using genetic algorithms with small populations. En S. Forrest (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, University of Illinois at Urbana-Champaign (pp. 92-99). San Mateo, USA: Morgan Kaufmann. Poincaré, H. (1908). Science et Méthode. Paris, France: Flammarion. Feng, J. and Chen, Y. (2010). Spatiotemporal evolution of urban form and land use structure in Hangzhou, China: Evidence from fractals. Environment and Planning B: Urban Analytics and City Science, 37, 838-856. de Vries, B. and Petersen, A. (2009). Conceptualizing sustainable development: An assessment methodology connecting values, knowledge, worldviews and scenarios. Ecological Economics, 68, 1006-1019. Chen, Y. and Wang, J. (2013). Multifractal characterization of urban form and growth: The case of Beijing. Environment and Planning B: Urban Analytics and City Science, 40, 884-904. 1 https://revistasojs.ucaldas.edu.co/index.php/virajes/article/view/3176 Revista de Antropología y Sociología : Virajes Universidad de Caldas application/pdf Artículo de revista Núm. 1 , Año 2018 : Enero - Junio 20 https://creativecommons.org/licenses/by/4.0 sostenibilidad simulación modelado sistemas complejos Luján Villar, Juan David Las tecnologías de investigación social son un conjunto de aplicaciones y modelos formales que posibilitan el abordaje de problemas sociales mediante métodos cuantitativos y cualitativos no necesariamente estadísticos, un gran campo iconológico de explicaciones visuales (Tufte, 1997), perspectivas transdisciplinares de conocimiento y ambientes de trabajo formal libres de disciplina. Este conjunto de aplicaciones presentan diversos retos y alternativas a los modelos mecánicos, estadísticos e interpretativos en estado puro de las ciencias sociales clásicas. El punto de partida de este trabajo enfatiza en la búsqueda de la sostenibilidad ecosistémica en escenarios urbanos y rurales y su investigación interdisciplinar, a propósito del impacto de las metodologías complejas, sus premisas, aplicaciones de trabajo práctico y conceptualizaciones básicas. Español Publication Revista de Antropología y Sociología: Virajes - 2018 Atmar, W. and Patterson, B.D. (1993). The Measure of Order and Disorder in the Distribution of Species in Fragmented Habitat. Oecologa, 96, 373-382. Chen, Y. and Feng, J. (2012). Fractal-based exponential distribution of urban density and self-affine fractal forms of cities. Chaos, Solitons & Fractals, 45, 1404-1416. Chen, S.H. and Yeh, C.H. (2002). On the Emergent Properties of Artificial Stock Markets: The Efficient Market Hypothesis and the Rational Expectations Hypothesis. Journal of Economic Behaviour and Organization, 49, 217-239. Cartozo, C.C., Garlaschelli, G. and Caldarelli, G. (2006). Graph Theory and Food Webs. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 93-117). New York, USA: Oxford University Press. Brand, S. (2010). Whole Earth Discipline: Why Dense Cities, Nuclear Power, Transgenic Crops, Restored Wildlands, Radical Science, and Geoengineering are Necessary. New York, USA: Atlantic Books. Bousquet, F. and Le Page, C. (2004). Multi-agent simulations and ecosystem management: A review. Ecol Modell, 176, 313-332. Borgatti, S. and Everett, M. (1999). Models of core/periphery structures. Social Networks, 21, 375-395. Booch, G., Rumbaugh, J. and Jacobson, I. (2005). The Unified Modeling Language User’s Guide. New York, USA: Addison-Wesley. Bascompte, J. and Jordana, P. (2006). The Structure of Plant-Animal M utualistic Networks. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 143-159). New York, USA: Oxford University Press. Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0. Batty, M. (2013). The New Science of Cities. Massachusetts, USA: The MIT Press. Ariza-Villaverde, A.B., Jiménez-Hornero, F.J. and Ravé, E.G.D. (2013). Multifractal analysis of axial maps applied to the study of urban morphology. Comput Environ Urban Systems, 38, 1-10. Amorim, L.M.E., Barros, M.N.M. and Cruz, D. (2014). Urban texture and space configuration: An essay on integrating socio spatial analytical techniques. Cities, 39, 58-67. complex systems Social sciences and sustainability: social research technologies applied to the urban and the rural Social research technologies are a set of applications and formal models that allow the approach of social problems through quantitative and qualitative methods not necessarily statistical, a large iconological field of visual explanations (Tufte, 1997), transdisciplinary perspectives of knowledge and free from any discipline formal work environments. This set of applications presents different challenges and alternatives to the mechanical, statistical and interpretative models in the pure state of the classical social sciences. The starting point of this work emphasizes the search for ecosystem sustainability in urban and rural settings and its interdisciplinary research regarding the impact of complex methodologies, their premises, applications of practical work and basic conceptualizations. sustainability simulation modeling Journal article https://doi.org/10.17151/rasv.2018.20.1.4 10.17151/rasv.2018.20.1.4 61 2018-01-01T00:00:00Z 2462-9782 81 https://revistasojs.ucaldas.edu.co/index.php/virajes/article/download/3176/2929 2018-01-01 2018-01-01T00:00:00Z 0123-4471 |
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UNIVERSIDAD DE CALDAS |
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Colombia |
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Revista de Antropología y Sociología : Virajes |
| title |
Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural |
| spellingShingle |
Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural Luján Villar, Juan David sostenibilidad simulación modelado sistemas complejos complex systems sustainability simulation modeling |
| title_short |
Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural |
| title_full |
Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural |
| title_fullStr |
Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural |
| title_full_unstemmed |
Ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural |
| title_sort |
ciencias sociales y sostenibilidad: tecnologías de investigación social aplicadas a lo urbano y lo rural |
| title_eng |
Social sciences and sustainability: social research technologies applied to the urban and the rural |
| description |
Las tecnologías de investigación social son un conjunto de aplicaciones y modelos formales que posibilitan el abordaje de problemas sociales mediante métodos cuantitativos y cualitativos no necesariamente estadísticos, un gran campo iconológico de explicaciones visuales (Tufte, 1997), perspectivas transdisciplinares de conocimiento y ambientes de trabajo formal libres de disciplina. Este conjunto de aplicaciones presentan diversos retos y alternativas a los modelos mecánicos, estadísticos e interpretativos en estado puro de las ciencias sociales clásicas. El punto de partida de este trabajo enfatiza en la búsqueda de la sostenibilidad ecosistémica en escenarios urbanos y rurales y su investigación interdisciplinar, a propósito del impacto de las metodologías complejas, sus premisas, aplicaciones de trabajo práctico y conceptualizaciones básicas.
|
| description_eng |
Social research technologies are a set of applications and formal models that allow the approach of social problems through quantitative and qualitative methods not necessarily statistical, a large iconological field of visual explanations (Tufte, 1997), transdisciplinary perspectives of knowledge and free from any discipline formal work environments. This set of applications presents different challenges and alternatives to the mechanical, statistical and interpretative models in the pure state of the classical social sciences. The starting point of this work emphasizes the search for ecosystem sustainability in urban and rural settings and its interdisciplinary research regarding the impact of complex methodologies, their premises, applications of practical work and basic conceptualizations.
|
| author |
Luján Villar, Juan David |
| author_facet |
Luján Villar, Juan David |
| topicspa_str_mv |
sostenibilidad simulación modelado sistemas complejos |
| topic |
sostenibilidad simulación modelado sistemas complejos complex systems sustainability simulation modeling |
| topic_facet |
sostenibilidad simulación modelado sistemas complejos complex systems sustainability simulation modeling |
| citationvolume |
20 |
| citationissue |
1 |
| citationedition |
Núm. 1 , Año 2018 : Enero - Junio |
| publisher |
Universidad de Caldas |
| ispartofjournal |
Revista de Antropología y Sociología : Virajes |
| source |
https://revistasojs.ucaldas.edu.co/index.php/virajes/article/view/3176 |
| language |
Español |
| format |
Article |
| rights |
http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0 Revista de Antropología y Sociología: Virajes - 2018 Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0. |
| references |
Kim, J., Lerch, F. and Simon, H.A. (1995). Internal representation and rule development in object-oriented design. ACM Transactions on Computer-Human Interaction, 2 (4), 357-390. Newell, A. (1990). Unified Theories of Cognition. Cambridge, USA: Harvard University Press. Murcott, A. (Ed.). (1983). The Sociology of Food and Eating: Essays on the Sociological Significance of Food. Aldershot, England: Gower. Moss, S. and Edmonds, B. (2005). Sociology and Simulation: Statistical and Qualitative Cross-Validation. AJS, 110 (4), 1095-1131. LeBaron, B., Arthur, W.B. and Palmer, R. (1999). Time Series Properties of an Artificial Stock Market. Journal of Economic Dynamics and Control, 23, 1487-1516. LeBaron, B. (2002). Short Memory Traders and Their Impact on Group Learning in Financial Markets. Proceedings of the U.S. National Academy of Sciences, 99, 7201-7206. Lansing, J.S. et al. (2017). Adaptive self-organization of Bali’s ancient rice terraces. Proceedings of the National Academy of Sciences, 114 (25), 6504-6509. Lansing, J.S. (2006). Perfect Order: Recognizing Complexity in Bali. New Jersey, USA: Princeton University Press. Klüver, J. (1996). Simulations of Self Organizing Social Systems. En F. Faulbaum and W. Bandilla (Ed.), SoftStat 95. Advances in Statistical Software (pp. 425-432). Stuttgart, Germany: Lucius. John, B.E., Vera, A.H. and Newell, A. (1994). Toward real-time GOMS: A model of expert behavior in a highly interactive task. Behavior and Information Technology, 13, 255-267. Northrop, R.B. and Connor, A.N. (2013). Ecological Sustainability. Understanding Complex Issues. Boca Raton, USA: CRC Press, Taylor & Francis Group. ICSU. (2016). A Draft Framework for Understanding SDG Interactions. Recuperado de https://icsu.org/cms/2017/05/SDG-interactions-working-paper.pdf. Holland, J. (1995). Hidden Order: How Adaptation Builds Complexity. Reading, England: Addison-Wesley. Higgins, A.J. et al. (2010). Applying operations research to agricultural value chain to achieve a balance in efficiency and resilience. Journal of the Operations Research Society, 61, 964-973. Harris, M. (1985). Good to Eat: Riddles of Food and Culture. New York, USA: Simon & Schuster. Gilbert, N., Ahrweiler, P. and Pyka, A. (Ed.). (2014). Simulating Knowledge Dynamics in Innovation Networks. Berlin, Germany: Springer-Verlag. Gilbert, N., Ahrweiler, P. and Pyka, A. (2010). The SKIN (Simulating Knowledge Dynamics in Innovation Networks) model. Mainz, Germany: Johannes Gutenberg University Mainz, University of Hohenheim. Gilbert, N. and Troitzsch, K.G. (2005). Simulation for the Social Scientist. Buckingham, United Kingdom: Open University Press. Frankhauser, P. (2015). From Fractal Urban Pattern Analysis to Fractal Urban Planning Concepts. En M. Helbich, J.J. Arsanjani and M. Leitner (Ed.), Computational Approaches for Urban Environments (pp. 13-48). Geneva, Switzerland: Springer International Publishing. Forrester, J. et al. (2014). Modeling Social-Ecological Problems in Coastal Ecosystems: A Case Study. Complexity, 19, 73-82. Nilsson, M., Griggs, D. and Visbeck, M. (2016). Map the interactions between Sustainable Development Goals. Nature, 534, 320-322. Pascual, M. and Dunne, J.A. (Ed.). (2006). Ecological Networks: Linking Structure to Dynamics in Food Webs. New York, USA: Oxford University Press. Egerton, F.N. (2007). Understanding food chains and food webs, 1700-1970. Bulletin of the Ecological Society of America, 88, 50-69. von Bertalanffy, L. (1976). Teoría general de los sistemas. Fundamentos, desarrollo, aplicaciones. Buenos Aires, Argentina: Fondo de Cultura Económica. Wilensky, U. and Rand, W. (2015). An Introduction to Agent-Based Modeling. Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, USA: The MIT Press. Wells, J. (2013). Complexity and Sustainability. New York, USA: Routledge. Tufte, E.R. (1997). Visual Explanations. Images and Quantities, Evidence and Narrative. Cheshire/ Connecticut, USA: Graphics Press. Pierce, W.D., Cushman, R.A. and Hood, C.E. (1912). The insect enemies of the cotton boll weevil. U.S. Department of Agriculture, Bureau of Entomology Bulletin, 100, 1-99. Suleiman, R., Troitzsch, K.G. and Gilbert, N. (Ed.). (2000). Tools and Techniques for Social Science Simulation. Heidelberg, Germany: Physica-Verlag. Sibertin-Blanc, C. et al. (2013). SocLab: A Framework for the Modeling, Simulation and Analysis of Power in Social Organizations. Journal of Artificial Societies and Social Simulation, 16 (4). Recuperado de http://jasss.soc.surrey.ac.uk/16/4/8.html. Salingaros, N.A. (2005). Principles of Urban Structure. Amsterdam, Netherlands: Techne Press. Schelling, T. (1978). Micromotives and Macrobehavior. New York, USA: Norton. Reynoso, C. (2013). Etnicidad y redes territoriales: perspectivas de complejidad. En B. Nates (Coord.), La frontera, las fronteras: diálogos transversales en estudios territoriales contemporáneos (pp. 63-90). Riohacha, Colombia: RETEC. Reynoso, C. (2006). Complejidad y caos: una exploración antropológica. Buenos Aires, Argentina: Editorial SB. Reynolds, R. and Kobti, Z. (2003). A Multi-Agent Simulation Using Cultural Algorithms: The Effect of Culture on the Resilience of Social Systems. Recuperado de http://ieeexplore.ieee.org/document/1299917/?reload=true. Reynolds, G.R. (1994). An Introduction to Cultural Algorithms. Recuperado de http://ai.cs.wayne.edu/ai/availablePapersOnLine/IntroToCA.pdf. Reeves, C.R. (1993). Using genetic algorithms with small populations. En S. Forrest (Ed.), Proceedings of the Fifth International Conference on Genetic Algorithms, University of Illinois at Urbana-Champaign (pp. 92-99). San Mateo, USA: Morgan Kaufmann. Poincaré, H. (1908). Science et Méthode. Paris, France: Flammarion. Feng, J. and Chen, Y. (2010). Spatiotemporal evolution of urban form and land use structure in Hangzhou, China: Evidence from fractals. Environment and Planning B: Urban Analytics and City Science, 37, 838-856. de Vries, B. and Petersen, A. (2009). Conceptualizing sustainable development: An assessment methodology connecting values, knowledge, worldviews and scenarios. Ecological Economics, 68, 1006-1019. Chen, Y. and Wang, J. (2013). Multifractal characterization of urban form and growth: The case of Beijing. Environment and Planning B: Urban Analytics and City Science, 40, 884-904. Atmar, W. and Patterson, B.D. (1993). The Measure of Order and Disorder in the Distribution of Species in Fragmented Habitat. Oecologa, 96, 373-382. Chen, Y. and Feng, J. (2012). Fractal-based exponential distribution of urban density and self-affine fractal forms of cities. Chaos, Solitons & Fractals, 45, 1404-1416. Chen, S.H. and Yeh, C.H. (2002). On the Emergent Properties of Artificial Stock Markets: The Efficient Market Hypothesis and the Rational Expectations Hypothesis. Journal of Economic Behaviour and Organization, 49, 217-239. Cartozo, C.C., Garlaschelli, G. and Caldarelli, G. (2006). Graph Theory and Food Webs. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 93-117). New York, USA: Oxford University Press. Brand, S. (2010). Whole Earth Discipline: Why Dense Cities, Nuclear Power, Transgenic Crops, Restored Wildlands, Radical Science, and Geoengineering are Necessary. New York, USA: Atlantic Books. Bousquet, F. and Le Page, C. (2004). Multi-agent simulations and ecosystem management: A review. Ecol Modell, 176, 313-332. Borgatti, S. and Everett, M. (1999). Models of core/periphery structures. Social Networks, 21, 375-395. Booch, G., Rumbaugh, J. and Jacobson, I. (2005). The Unified Modeling Language User’s Guide. New York, USA: Addison-Wesley. Bascompte, J. and Jordana, P. (2006). The Structure of Plant-Animal M utualistic Networks. En M. Pascual and J.A. Dunne (Ed.), Ecological Networks: Linking Structure to Dynamics in Food Webs (pp. 143-159). New York, USA: Oxford University Press. Batty, M. (2013). The New Science of Cities. Massachusetts, USA: The MIT Press. Ariza-Villaverde, A.B., Jiménez-Hornero, F.J. and Ravé, E.G.D. (2013). Multifractal analysis of axial maps applied to the study of urban morphology. Comput Environ Urban Systems, 38, 1-10. Amorim, L.M.E., Barros, M.N.M. and Cruz, D. (2014). Urban texture and space configuration: An essay on integrating socio spatial analytical techniques. Cities, 39, 58-67. |
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