A method for the automated construction of 3d models of cities and neighborhoods from official cadaster data for solar analysis

Beltran-Velamazan C. (Universidad de Zaragoza) ; Monzón-Chavarrías M. (Universidad de Zaragoza) ; López-Mesa B. (Universidad de Zaragoza)

Resumen: 3D city models are a useful tool to analyze the solar potential of neighborhoods and cities. These models are built from buildings footprints and elevation measurements. Footprints are widely available, but elevation datasets remain expensive and time-consuming to acquire. Our hypothesis is that the GIS cadastral data can be used to build a 3D model automatically, so that generating complete cities 3D models can be done in a short time with already available data. We propose a method for the automatic construction of 3D models of cities and neighborhoods from 2D cadastral data and study their usefulness for solar analysis by comparing the results with those from a hand-built model. The results show that the accuracy in evaluating solar access on pedestrian areas and solar potential on rooftops with the automatic method is close to that from the hand-built model with slight differences of 3.4% and 2.2%, respectively. On the other hand, time saving with the automatic models is significant. A neighborhood of 400, 000 m2 can be built up in 30 min, 50 times faster than by hand, and an entire city of 967 km2 can be built in 8.5 h. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Idioma: Inglés

DOI: 10.3390/su13116028

Año: 2021

Publicado en: Sustainability (Switzerland) 13, 11 (2021), 6028 [19 pp.]
ISSN: 2071-1050

Factor impacto JCR: 3.889 (2021)

Categ. JCR: ENVIRONMENTAL SCIENCES rank: 133 / 279 = 0.477 (2021) - Q2 - T2
Categ. JCR: ENVIRONMENTAL STUDIES rank: 57 / 128 = 0.445 (2021) - Q2 - T2
Categ. JCR: GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY rank: 35 / 47 = 0.745 (2021) - Q3 - T3
Categ. JCR: GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY rank: 7 / 9 = 0.778 (2021) - Q4 - T3

Factor impacto CITESCORE: 5.0 - Social Sciences (Q1) - Engineering (Q1) - Energy (Q2) - Environmental Science (Q1)

Factor impacto SCIMAGO: 0.664 - Energy Engineering and Power Technology (Q1) - Renewable Energy, Sustainability and the Environment (Q1) - Management, Monitoring, Policy and Law (Q1) - Geography, Planning and Development (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MICINN/PID2019-104871RB-C21

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Construc. Arquitectónicas (Dpto. Arquitectura)