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Influence of vegetation canopies on solar potential in urban environments

Abstract Solar energy is clearly a promising option among the many available sources of renewable energy, and its market has seen outstanding growth. Careful evaluation to determine suitable locations for photovoltaic installations is needed, however, as their efficiency is highly dependent on exposure to sun. Especially in urban environments, quantifying the shadows cast by other buildings and vegetation canopies may be essential. In the present study, we used light detection and ranging (LiDAR) data and geographic information systems (GIS) to assess the influence of shading vegetation on solar irradiation estimates in five European towns. The fraction of annual solar irradiation lost to shading by existing vegetation ranged between 3% and 11%. The fraction lost was higher in winter and lower in summer. Due to greater incoming solar radiation in summer, however, more than 50% of annual loss was accounted for in summer. We suggest that at the broad scale of whole cities the influence of vegetation on rooftop solar potential estimates is negligible (especially in densely populated areas). Analyses which do not consider vegetation because of data availability nevertheless provide valuable insight into localities' solar potential.
- Czech University of Life Sciences Prague Czech Republic
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).45 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
