Repositorio Institucional Universidad EAFIT ::Examinando por Autor "Duque, Juan C."

Examinando por Autor "Duque, Juan C."

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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.
An algorithmic approach for simulating realistic irregular lattices.
(Universidad EAFIT, 2013-07-12) Duque, Juan C.; Betancourt, Alejandro; Marin, Freddy
There is a wide variety of computational experiments, or statistical simulations, in which regional scientists require regular and irregular lattices with a predefined number of polygons. While most commercial and free GIS software offer the possibility of generating regular lattices of any size, the generation of instances of irregular lattices is not a straightforward task. The most common strategy in this case is to find a real map that matches as closely as possible the required number of polygons. This practice is usually conducted without considering whether the topological characteristics of the selected map are close to those for an “average” map sampled in different parts of the world. In this paper, we propose an algorithm, RI-Maps, that combines fractal theory, stochastic calculus and computational geometry for simulating realistic irregular lattices with a predefined number of polygons. The irregular lattices generated with RI-Maps have guaranteed consistency in their topological characteristics, which reduces the potential distortions in the computational or statistical results due to an inappropriate selection of the lattices.
Análisis de la distribución espacial de la reducción en la demanda de agua potable como efecto de políticas de ahorro en su consumo en el Área Metropolitana del Valle de Aburrá.
(Universidad EAFIT, 2013-08-08) Duque, Juan C.; Gutiérrez, Diana C.; Betancourt, Alejandro; Patiño, Jorge
El presente estudio presenta un análisis, espacialmente desagregado, de la disminución en el consumo residencial de agua en el Área Metropolitana del Valle de Aburrá (AMVA) durante el periodo 2005 – 2010 e identificar las características socioeconómicas asociadas a estos patrones. Además, se analiza la forma cómo las políticas y campañas para incentivar la disminución del consumo de agua potable han sido acogidas en el AMVA. Los resultados obtenidos muestran claras diferencias espaciales (y por estrato) en los niveles de consumo de agua, así como en los niveles de reducción de dicho consumo en el período analizado. También, por medio de modelos de econometría espacial, se encuentra que las características socioeconómicas juegan un papel relevante a la hora de explicar los niveles de consumo de agua y que estos consumos presentan autocorrelación espacial sustantiva que indica que los niveles de consumo de agua potable en un área determinada no solo dependen de las características socioeconómicas del área, sino también de los niveles de consumo de las áreas vecinas. Por último, se encuentra que los impactos derivados del desincentivo económico al consumo excesivo, tiene un efecto inmediato que no perdura en el tiempo
A computationally efficient method for delineating irregularly shaped spatial clusters
(Springer Berlin Heidelberg, 2011-12-01) Duque, Juan C.; Aldstadt, Jared; Velasquez, Ermilson; Franco, Jose L.; Betancourt, Alejandro; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
In this paper, we present an efficiency improvement for the algorithm called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, devised by Aldstadt and Getis (Geogr Anal 38(4):327-343, 2006). AMOEBA embeds a local spatial autocorrelation statistic in an iterative procedure in order to identify spatial clusters (ecotopes) of related spatial units. We provide an analysis of the computational complexity of the original AMOEBA and develop an alternative formulation that reduces computational time without losing optimality. Empirical evidence is provided using georeferenced socio-demographic data in Accra, Ghana. © 2010 Springer-Verlag.
The Determinants of UN Interventions. Are There Regional Preferences?
(Universidad EAFIT, 2013-04-14) Duque, Juan C.; Jetter, Michael; Sosa, Santiago
What leads the United Nations Security Council to intervene in one conflict, but remain inactive in others of similar magnitude and cruelty? This paper analyzes all registered 178 internal and internationalized internal conflicts since 1945, with the goal to unveil what determines the probability of a UN intervention. Our main focus lies on the question whether the geographical proximity to the ve permanent members of the UN Security Council (China,France, Russia, the United Kingdom, and the United States) has an e ect on the probability of intervention. Our results suggest that the UN is substantially more likely to intervene in conflicts located in Europe. A more detailed look at distances revels that for every 1,000 kilometers of distance from France or the United Kingdom the probability of intervention decreases by about one third. Further, we nd that UN intervention is signi cantly more likely to happen in smaller (less population), poorer (smaller GDP per capita), and less open economies (openness to international trade).
Diez años de atentados a la infraestructura de Colombia
(Centro De Análisis Político – Universidad EAFIT, 2009) Villegas, L. C.; Duque, Juan C.; 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)
HouSI: Heuristic for delimitation of housing submarkets and price homogeneous areas
(ELSEVIER SCI LTD, 2013-01-01) Royuela, V.; Duque, Juan C.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
This paper seeks to address the problem of the empirical identification of housing market segmentation, once we assume that submarkets exist. The typical difficulty in identifying housing submarkets when dealing with many locations is the vast number of potential solutions and, in such cases, the use of the Chow test for hedonic functions is not a practical solution. Here, we solve this problem by undertaking an identification process with a heuristic for spatially constrained clustering, the "Housing Submarket Identifier" (HouSI). The solution is applied to the housing market in the city of Barcelona (Spain), where we estimate a hedonic model for fifty thousand dwellings aggregated into ten groups. In order to determine the utility of the procedure we seek to verify whether the final solution provided by the heuristic is comparable with the division of the city into ten administrative districts. © 2012 Elsevier Ltd.
Intención de abandono en estudiantes de pregrado: factores y soluciones
(Universidad EAFIT, 2014-06-16) Duque, Juan C.; Montes, Isabel; Rodríguez, Stefanía; Jaramillo, Alberto; jduquec1@eafit.edu.co; imontesg@eafit.edu.co; srodrig7@eafit.edu.co; ajarami@eafit.edu.co
The present study addressed dropout intention problem from a priori perspective. Conceptually and methodologically it was based on Suriñach et al (2007), Duque et al (2012), Duque (2013a) y Duque (2013b). Measuring the effect from satisfaction and academic development to dropout intentions was the main purpose. To achieve this objective, we applied a survey with active students from all undergraduate programs at Universidad EAFIT. The analysis was carried out through structural equations based on the partial least squares algorithm (PLS). The results show that, on average, the effect is 0.38. It means that if students’ satisfaction would increase in one unit, dropout intention reduced in 0.25. At the same way, we found that better learning outcome perceptions (cognitive and affective), students decrease their dropout intention in 0.25.
Is the wage curve formal or informal? Evidence for Colombia
(ELSEVIER SCIENCE SA, 2010-11-01) Ramos, Raul; Duque, Juan C.; Surinach, Jordi; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
Using microdata from the 2002-2006 Colombian Continuous Household Survey, we find an elasticity of individual wages to local unemployment rates of - 0.07. However, the elasticity for informal workers is significantly higher, a result which is consistent with efficiency wage theoretical models and relevant for regional labour market analysis in developing countries. © 2010 Elsevier B.V.
Learning outcomes and dropout intentions: An analytical model for Spanish universities
(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2013-07-01) Duque, Lola C.; Duque, Juan C.; Surinach, Jordi; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
The dropout rate among Spanish university students is very high compared to the European mean, creating a pressing need for the introduction of policies and programmes aimed at increasing rates of persistence. In this article, we study this problem by combining students' perceived learning outcomes with their dropout intentions, and we propose a research model that considers subjective factors that might impact this decision. The model is estimated for two degree courses: Business Administration and Nursing. The estimation method uses structural equations based on the partial least squares algorithm. This allows the construction of indices for the variables of interest, enabling us to make comparisons between courses and over time. To reduce dropout intentions, efforts need to be focused on obtaining better cognitive outcomes, as well as on achieving a higher level of student satisfaction with their university experience. © 2013 Copyright Taylor and Francis Group, LLC.
The Max-p-region problem
(Wiley-Blackwell, 2012-08) Duque, Juan C.; Ansellin, Luc; Rey, Sergio; Universidad EAFIT. Escuela de Economía y Finanzas. Research in Spatial Economics (RiSE), Carrera 49 7 Sur-50, Medellín, Colombia.; GeoDa Center for Geospatial Analysis and Computation, School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287-5302; Universidad EAFIT. Departamento de Economía y Finanzas; Duque, Juan C. (jduquec1@eafit.edu.co); Research in Spatial Economics (RiSE); Research in Spatial Economics (RISE)
In this paper, we introduce a new spatially constrained clustering problem called the max-p-regions problem. It involves the clustering of a set of geographic areas into the maximum number of homogeneous regions such that the value of a spatially extensive regional attribute is above a predefined threshold value.We formulate the max-p-regions problem as a mixed integer programming (MIP) problem, and propose a heuristic solution.
Measuring intra-urban poverty using land cover and texture metrics derived from remote sensing data
(ELSEVIER SCIENCE BV, 2015-03-01) Duque, Juan C.; Patino, Jorge E.; Ruiz, Luis A.; Pardo-Pascual, Josep E.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
This paper contributes empirical evidence about the usefulness of remote sensing imagery to quantify the degree of poverty at the intra-urban scale. This concept is based on two premises: first, that the physical appearance of an urban settlement is a reflection of the society; and second, that the people who reside in urban areas with similar physical housing conditions have similar social and demographic characteristics. We use a very high spatial resolution (VHR) image from one of the most socioeconomically divergent cities in the world, Medellin (Colombia), to extract information on land cover composition using per-pixel classification and on urban texture and structure using an automated tool for texture and structure feature extraction at object level. We evaluate the potential of these descriptors to explain a measure of poverty known as the Slum Index. We found that these variables explain up to 59% of the variability in the Slum Index. Similar approaches could be used to lower the cost of socioeconomic surveys by developing an econometric model from a sample and applying that model to the rest of the city and to perform intercensal or intersurvey estimates of intra-urban Slum Index maps. (C) 2014 Elsevier B.V. All rights reserved.
The p-Regions Problem
(WILEY-BLACKWELL, 2011-01-01) Duque, Juan C.; Church, Richard L.; Middleton, Richard S.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
The p-regions problem involves the aggregation or clustering of n small areas into p spatially contiguous regions while optimizing some criteria. The main objective of this article is to explore possible avenues for formulating this problem as a mixed integer-programming (MIP) problem. The critical issue in formulating this problem is to ensure that each region is a spatially contiguous cluster of small areas. We introduce three MIP models for solving the p regions problem. Each model minimizes the sum of dissimilarities between all pairs of areas within each region while guaranteeing contiguity. Three strategies designed to ensure contiguity are presented: (1) an adaptation of the Miller, Tucker, and Zemlin tour-breaking constraints developed for the traveling salesman problem; (2) the use of ordered-area assignment variables based upon an extension of an approach by Cova and Church for the geographical site design problem; and (3) the use of flow constraints based upon an extension of work by Shirabe. We test the efficacy of each formulation as well as specify a strategy to reduce overall problem size. © 2011 The Ohio State University.
Quantifying slumness with remote sensing data
(Universidad EAFIT, 2013-08-08) Duque, Juan C.; Patino, Jorge E.; Ruiz, Luis A.; Pardo-Pascual, Josep E.
The presence of slums in a city is an indicator of poverty and its proper delimitation is a matter of interest for researchers and policy makers. Socio-economic data from surveys and censuses are the primary source of information to identify and quantify slumness within a city or a town. One problem of using survey data for quantifying slumness is that this type of data is usually collected every ten years and is an expensive and time consuming process. Based on the premise that the physical appearance of an urban settlement is a reflection of the society that created it and on the assumption that people living in urban areas with similar physical housing conditions will have similar social and demographic characteristics (Jain, 2008; Taubenb¨ock et al., 2009b); this paper uses data from Medellin City, Colombia, to estimate slum index using solely remote sensing data from an orthorectified, pan-sharpened, natural color Quickbird scene. For Medellin city, the percentage of clay roofs cover and the mean swimming pool density at the analytical region level can explain up to 59% of the variability in the slum index. Structure and texture measures are useful to characterize the differences in the homogeneity of the spatial pattern of the urban layout and they improve the explanatory power of the statistical models when taken into account. When no other information is used, they can explain up to 30% of the variability of the slum index. The results of this research are encouraging and many researchers, urban planners and policy makers could benefit from this rapid and low cost approach to characterize the intra-urban variations of slumness in cities with sparse data or no data at all.
UN interventions: The role of geography
(SPRINGER, 2015-03-01) Duque, Juan C.; Jetter, Michael; Sosa, Santiago; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
This paper argues that UN military interventions are geographically biased. For every 1,000 kilometers of distance from the three permanent Western UNSC members (France, UK, US), the probability of a UN military intervention decreases by 4 percent. We are able to rule out several alternative explanations for the distance finding, such as differences by continent, colonial origin, bilateral trade relationships, foreign aid flows, political regime forms, or the characteristics of the Cold War. We do not observe this geographical bias for non-military interventions, providing evidence that practical considerations could be important factors for UNSC decisions to intervene militarily. In fact, UNSC interventions are also more likely in smaller and poorer countries - both of which are indications of less costly interventions and higher chances of success, everything else equal.
Using remote sensing to assess the relationship between crime and the urban layout
(ELSEVIER SCI LTD, 2014-12-01) Patino, Jorge E.; Duque, Juan C.; Pardo-Pascual, Josep E.; Ruiz, Luis A.; Universidad EAFIT. Departamento de Economía y Finanzas; Research in Spatial Economics (RISE)
The link between place and crime is at the base of social ecology theories of crime that focus in the relationship of the characteristics of geographical areas and crime rates. The broken windows theory states that visible cues of physical and social disorder in a neighborhood can lead to an increase in more serious crime. The crime prevention through environmental design (CPTED) planning approach seeks to deter criminal behavior by creating defensible spaces. Based on the premise that a settlement's appearance is a reflection of the society, we ask whether a neighborhood's design has a quantifiable imprint when seen from space using urban fabric descriptors computed from very high spatial-resolution imagery. We tested which land cover, structure and texture descriptors were significantly related to intra-urban homicide rates in Medellin, Colombia, while controlling for socioeconomic confounders. The percentage of impervious surfaces other than clay roofs, the fraction of clay roofs to impervious surfaces, two structure descriptors related to the homogeneity of the urban layout, and the uniformity texture descriptor were all statistically significant. Areas with higher homicide rates tended to have higher local variation and less general homogeneity; that is, the urban layouts were more crowded and cluttered, with small dwellings with different roofing materials located in close proximity to one another, and these regions often lacked other homogeneous surfaces such as open green spaces, wide roads, or large facilities. These results seem to be in agreement with the broken windows theory and CPTED in the sense that more heterogeneous and disordered urban layouts are associated with higher homicide rates. © 2014 Elsevier Ltd.

Examinando por Autor "Duque, Juan C."

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