Reciclado masivo de la envolvente urbano-edilicia basado en procesamiento digital de imágenes, La Plata, Argentina
; Barbero, Dante Andrés
; Chevez, Pedro Joaquín
; Martini, Irene
; Discoli, Carlos Alberto 
Otros responsables
Fecha
2020-12-01
Editorial
Universidad de Chile. Facultad de Arquitectura y Urbanismo
Revista
Revista de Urbanismo
Título del libro
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Fecha del evento
Institución organizadora
ISSN
0717-5051
eISSN
ISBN
Idioma
Español
Tipo del evento
Clasificación temática
Resumen
El presente trabajo busca generar soluciones para abordar la problemática del reciclado edilicio masivo del sector residencial a nivel urbano. Para ello, se desarrolla una metodología innovadora orientada a identificar los distintos materiales constructivos de la envolvente urbana-edilicia para realizar estimaciones de ahorro de energía por incorporación de eficiencia energética. Se propone el procesamiento digital de imágenes satelitales SPOT 6 y aéreas a través de clasificaciones. En este caso se clasifican los techos; se determina la calidad de los resultados; y sobre los mejores resultados se aplican estrategias de mejora de la envolvente para su tratamiento masivo a escala urbana. Como caso de aplicación se trabajó con el sector residencial del partido de La Plata, Argentina. Los resultados mostraron que las clasificaciones con imágenes aéreas alcanzan una buena precisión para la complejidad urbana abordada (70 %). Esto permitió estimar la potencialidad de ahorros de energía anual para calefacción entre 2000 y 3000 kWh/año por vivienda, visualizados en forma ágil por medio de cartografía urbana. En efecto, el uso de sensores remotos aplicados al análisis detallado y masivo de áreas urbanas aporta un conocimiento de interés y poco difundido en nuestra región. A su vez, esta metodología puede ser extrapolada a ciudades con características análogas.
The purpose of this work is to provide solutions for mass retrofitting of building envelope in residential areas at urban level. An innovative methodology is developed that identify the different construction materials of the urban-building envelope in large-scale to estimate energy saving by recycling them with energy efficiency criteria. It is proposed the digital processing of SPOT 6 satellite and aerial images through semi-automatic classifications. In this case, the roofs are classified, the quality of the results is determined, the most appropriate processing is defined, and with these results envelope improvement strategies are applied for mass treatment at urban level. The work was carried out in the residential area of La Plata department, Argentina. The results showed that the classifications with aerial images achieve good precision for the complexity addressed (70%). This allowed estimating energy savings which can be seen on urban maps easily showing the annual energy saving potentialities for heating between 2000 and 3000 kWh/year per house. In effect, the use of remote sensors applied to the detailed and massive analysis of urban sectors provides a little disseminated knowledge of interest in our region. In turn, this methodology can be applied to cities with similar characteristics.
The purpose of this work is to provide solutions for mass retrofitting of building envelope in residential areas at urban level. An innovative methodology is developed that identify the different construction materials of the urban-building envelope in large-scale to estimate energy saving by recycling them with energy efficiency criteria. It is proposed the digital processing of SPOT 6 satellite and aerial images through semi-automatic classifications. In this case, the roofs are classified, the quality of the results is determined, the most appropriate processing is defined, and with these results envelope improvement strategies are applied for mass treatment at urban level. The work was carried out in the residential area of La Plata department, Argentina. The results showed that the classifications with aerial images achieve good precision for the complexity addressed (70%). This allowed estimating energy savings which can be seen on urban maps easily showing the annual energy saving potentialities for heating between 2000 and 3000 kWh/year per house. In effect, the use of remote sensors applied to the detailed and massive analysis of urban sectors provides a little disseminated knowledge of interest in our region. In turn, this methodology can be applied to cities with similar characteristics.
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