Mauricio Rincon-Romero | Universidad del Valle - Colombia (original) (raw)
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Papers by Mauricio Rincon-Romero
Revista EIA
Desde el concepto de Ciudad Inteligente se abstrae a un modelo de Campus Inteligente, soportado p... more Desde el concepto de Ciudad Inteligente se abstrae a un modelo de Campus Inteligente, soportado por geoinformación y tecnologías de la información y la comunicación para generar una herramienta de apoyo a la movilidad dentro del Campus universitario. Las preguntas a resolver con la herramienta son: “en dónde queda”, y “cómo llego a”. Adoptando un Campus de 100 hectáreas y 18 kilómetros de caminos y vías, son dispuestos en una base de datos espacial para un Sistema de Información Geográfica y se dispone a través de una aplicación móvil y Web. Después de introducir los parámetros de la consulta al sistema, se construye la respuesta identificando el destino y cómo llegar a él, a través de la ruta más corta sobre el mapa base de la Universidad del Valle, la distancia entre los puntos origen-destino y el tiempo de recorrido para un peatón entre ellos. El Sig Web se desarrolló con Geoserver como servidor de mapas articulado con la librería Leaflet para JavaScript, usando un motor de base ...
Digital Soil Mapping with Limited Data, 2008
Revista Brasileira De Epidemiologia, 2009
Despite much research in the identification of areas with malaria, it is urgent to further invest... more Despite much research in the identification of areas with malaria, it is urgent to further investigate mapping techniques to achieve better approaches in strategies to prevent, mitigate, and eradicate the mosquito and the illness eventually. By using spatial distributed modeling techniques with Geographical Information Systems (GIS), the study proposes methodology to map malaria risk zoning for the municipality of Buenaventura in Colombia. The model proposed by Craig et al.1 using climatic information was adapted to the conditions of the study area regarding scale and spatial resolution. Geomorphologic and anthropic variables were added to improve spatial allocation of areas with higher risk of contracting the illness, refining zoning. Then, they were contrasted with the locations reported by health entities2, taking into account spatial distribution. The comparison of results shows a decrease in the area obtained initially using the Craig et al. model1 (1999), from 5,422.4 km2 (89.1% of the municipality's territory) to 624.3km2 (approximately 10% of the municipality's area), yielding a total reduction of 78.8% when environmental and anthropic variables were included in the model. Data show that of the 9,863 cases reported during 2001 to 2005 for 20 selected towns as basis for the amount of surveyed malaria cases2, 1,132 were located in the very high-risk areas, 7,662 were in the areas of moderate risk, and 1,066 cases in low-risk areas, showing that 89% of the cases reported fell into the areas with higher risk for malaria.
Revista EIA
Desde el concepto de Ciudad Inteligente se abstrae a un modelo de Campus Inteligente, soportado p... more Desde el concepto de Ciudad Inteligente se abstrae a un modelo de Campus Inteligente, soportado por geoinformación y tecnologías de la información y la comunicación para generar una herramienta de apoyo a la movilidad dentro del Campus universitario. Las preguntas a resolver con la herramienta son: “en dónde queda”, y “cómo llego a”. Adoptando un Campus de 100 hectáreas y 18 kilómetros de caminos y vías, son dispuestos en una base de datos espacial para un Sistema de Información Geográfica y se dispone a través de una aplicación móvil y Web. Después de introducir los parámetros de la consulta al sistema, se construye la respuesta identificando el destino y cómo llegar a él, a través de la ruta más corta sobre el mapa base de la Universidad del Valle, la distancia entre los puntos origen-destino y el tiempo de recorrido para un peatón entre ellos. El Sig Web se desarrolló con Geoserver como servidor de mapas articulado con la librería Leaflet para JavaScript, usando un motor de base ...
Digital Soil Mapping with Limited Data, 2008
Revista Brasileira De Epidemiologia, 2009
Despite much research in the identification of areas with malaria, it is urgent to further invest... more Despite much research in the identification of areas with malaria, it is urgent to further investigate mapping techniques to achieve better approaches in strategies to prevent, mitigate, and eradicate the mosquito and the illness eventually. By using spatial distributed modeling techniques with Geographical Information Systems (GIS), the study proposes methodology to map malaria risk zoning for the municipality of Buenaventura in Colombia. The model proposed by Craig et al.1 using climatic information was adapted to the conditions of the study area regarding scale and spatial resolution. Geomorphologic and anthropic variables were added to improve spatial allocation of areas with higher risk of contracting the illness, refining zoning. Then, they were contrasted with the locations reported by health entities2, taking into account spatial distribution. The comparison of results shows a decrease in the area obtained initially using the Craig et al. model1 (1999), from 5,422.4 km2 (89.1% of the municipality's territory) to 624.3km2 (approximately 10% of the municipality's area), yielding a total reduction of 78.8% when environmental and anthropic variables were included in the model. Data show that of the 9,863 cases reported during 2001 to 2005 for 20 selected towns as basis for the amount of surveyed malaria cases2, 1,132 were located in the very high-risk areas, 7,662 were in the areas of moderate risk, and 1,066 cases in low-risk areas, showing that 89% of the cases reported fell into the areas with higher risk for malaria.