Research in Spatial Economics (RISE)

URI permanente para esta comunidad

https://hdl.handle.net/10784/28017

In our group we develop quantitative methods for spatial analysis that allow researchers, public and private institutions to attain a better understanding of their georeferenced data. Our methodologies are characterized by their multidisciplinarity, involving research domains such as operation research, econometrics and exploratory spatial data analysis.

Líneas de investigación: Algoritmos y Métodos Computacionales; Econometría Espacial y Sistemas; Información Geográfica.
Código Minciencias: COL0079819.
Categoría 2019: A1.
Escuela: Ciencias.
Coordinadora: Juan Carlos Duque Cardona.
Correo electrónico: jduquec1@eafit.edu.co

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Mostrando 1 - 20 de 101

A network based approach towards industry clustering
(Edward Elgar Publishing Ltd, 2008) Duque, Juan C.; Rey, S. J.; Universidad EAFIT. Escuela de Economía y Finanzas. Research in Spatial Economics (RiSE), Carrera 49 7 Sur-50, Medellín, Colombia.; Escuela de Economía y Finanzas; Duque, Juan C. (jduquec1@eafit.edu.co); Research in Spatial Economics (RiSE)
A review of regional science applications of satellite remote sensing in urban settings
(Elsevier Sci Ltd, 2013-01) Patino, J. E.; Duque, Juan C.; Universidad EAFIT. Escuela de Economía y Finanzas. Research in Spatial Economics (RiSE), Carrera 49 7 Sur-50, Medellín, Colombia.; Universidad EAFIT. Departamento de Economía y Finanzas; Patino, J.E. (jpatinoq@eafit.edu.co); Duque, Juan C. (jduquec1@eafit.edu.co); Research in Spatial Economics (RiSE); Research in Spatial Economics (RISE)
This paper reviews the potential applications of satellite remote sensing to regional science research in urban settings. Regional science is the study of social problems that have a spatial dimension. The availability of satellite remote sensing data has increased significantly in the last two decades, and these data constitute a useful data source for mapping the composition of urban settings and analyzing changes over time. The increasing spatial resolution of commercial satellite imagery has influenced the emergence of new research and applications of regional science in urban settlements because it is now possible to identify individual objects of the urban fabric. The most common applications found in the literature are the detection of urban deprivation hot spots, quality of life index assessment, urban growth analysis, house value estimation, urban population estimation and urban social vulnerability assessment. The satellite remote sensing imagery used in these applications has medium, high or very high spatial resolution, such as images from Landsat MSS, Landsat TM and ETM+, SPOT, ASTER, IRS, Ikonos and QuickBird. Consistent relationships between socio-economic variables derived from censuses and field surveys and proxy variables of vegetation coverage measured from satellite remote sensing data have been found in several cities in the US. Different approaches and techniques have been applied successfully around the world, but local research is always needed to account for the unique elements of each place. Spectral mixture analysis, object-oriented classifications and image texture measures are some of the techniques of image processing that have been implemented with good results. Many regional scientists remain skeptical that satellite remote sensing will produce useful information for their work. More local research is needed to demonstrate the real potential and utility of satellite remote sensing for regional science in urban environments.
A Stepwise Procedure to Determinate a Suitable Scale for the Spatial Delimitation of Urban Slums
(2012-01-01) Duque, Juan Carlos
A stepwise procedure to determinate a suitable scale for the spatial delimitation of urban slums
(SPRINGER, 2012-01-01) Duque JC; Royuela, Vicente; Noreña, Miguel
A stepwise procedure to determinate a suitable scale for the spatial delimitation of urban slums
(Springer Nature, 2012-01-01) Duque, J.C.; Royuela, V.; Noreña, M.
The globalisation era in which we live has made the world an interconnected space with several global trends. We find developing countries with very high growth rates, what helps to find world economic convergence. As a complement to this trend, within those countries there is a dramatic growth pattern of cities into megacities, as economic activity concentrates in space to exploit agglomeration economies. According to UN-Habitat, in the next two decades the global population living in urban areas will move from 50 % to 70 %. © Springer-Verlag Berlin Heidelberg 2012.
A stepwise tool for spatial delineation of marginal areas. Medellin (Colombia) as a case study
(SPRINGER, 2015-04-16) Duque, Juan Carlos
Agglomeration Economies in the Presence of an Informal Sector The Colombian Case
(ARMAND COLIN, 2019-04-30) Garcia, Gustavo Adolfo; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Agglomeration economies in the presence of an informal sector: the Colombian case
(ARMAND COLIN, 2019-01-01) Garcia, Gustavo A.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
This paper analyzes the relationship between agglomeration economies and productivity in the context of a developing country in presence of an informal sector. Using data from Colombia, we examine whether the informal sector achieves benefits from agglomeration economies as well as whether there are differences between the formal and informal sectors in terms of agglomeration returns. We find that agglomeration economies have a significantly positive effect on productivity in the informal sector: informal workers in denser areas will earn approximately 11% more than those in less dense areas.
Algunos conceptos de la econometría espacial y el análisis exploratorio de datos espaciales.
(Universidad EAFIT, 2008-10-01) Acevedo, Ingrid; Velásquez, H.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
El presente artículo es parte del trabajo realizado en el proyecto de Investigación ?Análisis Exploratorio de Datos Espaciales y el Índice de Moran?, el cual es financiado con fondos de la Universidad EAFIT para el año 2008. En este trabajo se presenta
Alternativas fundamentales para cuantificar el riesgo operacional
(Universidad EAFIT, 2010-01-01) Velasquez, Hermilson; Luis Ceferino Franco Arbeláez; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Análisis del índice general de la bolsa de valores de colombia y sus rendimientos desde la teoría del caos, 2001-2011
(Universidad de Medellín, 2012-01-01) Velasquez, Hermilson; Restrepo, Jorge Humberto; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
El objetivo de este trabajo es presentar un enfoque alternativo para el análisis de las seriesde tiempo en mercados financieros, cuyos fundamentos consideran la posible existencia decaracterísticas de objetos...
Análisis espacial cuantitativo de la transformación de humedales continentales en Colombia
(2016-06-01) Patiño, Jorge Eduardo; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Análisis espacial de la informalidad laboral intraurbana
(2018-12-01) Garcia, Gustavo Adolfo; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Análisis espacial de la informalidad laboral intraurbana en Medellín
(2018-12-15) Garcia, G.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Analyzing Long-Term Availability of Urban Green Space by Socioeconomic Status in Medellin, Colombia, Using Open Data and Tools
(Institute of Electrical and Electronics Engineers Inc., 2020-01-01) Patino J.E.; Patino J.E.; Universidad EAFIT. Departamento de Ciencias; Research in Spatial Economics (RISE)
The availability of green spaces is an important issue for urban populations worldwide, given the benefits that the green spaces provide for health, well-being, and quality of life. But urban green spaces are not always distributed equally for different population groups within cities. Latin America is the second most urbanized region of the world, but there are few published studies analysing the green space availability for different urban population groups, and less so analysing the long-term trends. This work presents an analysis of long-term availability of urban green spaces by different socioeconomic status population groups in Medellin city, Colombia, using open geospatial data and open software tools. The results indicate that disparities between different groups have been decreasing in the last years, but there are still efforts to do. Showing this kind of analysis based on open data and tools is essential as it opens the possibility for replicating it in other cities with scarce budgets. © 2020 IEEE.
Una aplicación con datos de sobrevivencia: Utilización de modelos de regresión parcial censurados
(Fondo Editorial Universidad EAFIT, 2010-12-31) Velasquez, Hermilson; Héctor Javier Herrera; Jorge Ivan Jimenez Gomez; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Arbitrage pricing theory
(Editorial Académica Española, 2014-09-30) Velasquez, Hermilson; CARLOS DANIEL ARANGO RESTREPO; Velasquez, Hermilson; CARLOS DANIEL ARANGO RESTREPO; Universidad EAFIT. Departamento de Ciencias; Research in Spatial Economics (RISE)
Automatic detection of building typology using deep learning methods on street level images
(PERGAMON-ELSEVIER SCIENCE LTD, 2020-03-20) Duque, J.; Gonzalez, D.; Rueda Plata, Diego; Acevedo, A.; Ramos, R.; Betancourt, A.; García, S.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
An exposure model is a key component for assessing potential human and economic losses from natural disasters. An exposure model consists of a spatially disaggregated description of the infrastructure and population of a region under study. Depending on the size of the settlement area, developing such models can be a costly and time-consuming task. In this paper we use a manually annotated dataset consisting of approximately 10,000 photos acquired at street level in the urban area of Medellín to explore the potential for using a convolutional neural network (CNN) to automatically detect building materials and types of lateral-load resisting systems, which are attributes that define a building's structural typology (which is a key issue in exposure models for seismic risk assessment). The results of the developed model achieved a precision of 93% and a recall of 95% when identifying nonductile buildings, which are the buildings most likely to be damaged in an earthquake. Identifying fine-grained material typology is more difficult, because many visual clues are physically hidden, but our model matches expert level performances, achieving a recall of 85% and accuracy scores ranging from 60% to 82% on the three most common building typologies, which account for 91% of the total building population in Medellín. Overall, this study shows that a CNN can make a substantial contribution to developing cost-effective exposure models. © 2020 Elsevier Ltd
Book review: Emilio Chuvieco, Fundamentals of satellite remote sensing: An environmental approach. 2nd ed. CRC Res: Boca Raton, FL, 2016. 468 pp. ISBN 9781498728058. $ 79.96 (Hardback), 69.97 (eBook).
(2017-04-01) Patiño, Jorge Eduardo; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Capacidades de emprendimiento corporativo y su impacto en los proyectos innovadores.
(2016-07-10) Cardona, Raul Armando; Velasquez C, Hermilson; Martins, I.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
La importancia del emprendimiento corporativo ha sido ampliamente estudiada, debido a los impactos en la sostenibilidad, crecimiento, renovación estratégica, productividad e innovación empresarial.

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