Spatial assessment of buildings energy consumption based on three-dimensional modeling of the urban environment
Abstract
The article deals with the application of spatial assessment of urban buildings energy consumption (EC) and analyzing the results based on the urbogeosystems approach. Assessment of buildings EC involves establishing a correlation between their EC and the relevant geometric characteristics, in particular, the buildings height and volume. The authors propose the use of remote laser scanning data (LiDAR data) for the automated extraction of these characteristics of buildings with high accuracy.
An original approach to processing and analyzing LiDAR data using the tools of the author's web-based GIS application for the purpose of buildings extraction and modeling is presented. The extracted building models contain their exact geometric characteristics and generalized architectural properties as attributes.
The article presents a methodology for calculating the EC of buildings, which uses their geometric information, as well as information on their age and type, which are also correlated with the buildings EC. Based on the buildings geometry obtained from LiDAR data, the indicator of their usable area (intended for heating) is determined. To estimate EC, data on the buildings EC are taken from real meter readings, which are extrapolated to the calculated indicator of the buildings usable area. A semantic table is created that corrects the calculated building EC, depending on its age and type, and determines the final energy efficiency class of the building.
According to the above methods, three-dimensional models of buildings for the cities of Amsterdam and Eindhoven were extracted and visualized, with the color scheme applied to the buildings reflecting their energy efficiency classes. The essence of the urbogeosystemic analysis of the urban environment in the context of the urban EC study is revealed. On the basis of the obtained visualization of the spatial distribution of urban EC, certain regularities of such distribution between individual urban buildings are identified and the factors influencing the level of this indicator are determined.
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References
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Copyright (c) 2023 Денис Серьогін, Сергій Костріков
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