Viewshed-based modelling of visual exposure to urban greenery – An efficient GIS tool for practical planning applications

Abstract

Quantifying green visual exposure is necessary to assess aesthetic, social and health benefits from urban greenery. Viewshed analysis has been successfully used to model and map green visual exposure from human perspective in continuous representation and in places where street view imagery for widely-used photography-based methods is not available. However, current viewshed-based methods for modelling green visual exposure are often difficult to generalise beyond their specific application purpose, inefficient in processing large spatial extents and have limited use due to demands on technical knowledge. This hampers their wider use in research and practice. In this paper, we develop a viewshed analysis-based method for modelling visual exposure to urban greenery with special focus on the method’s applicability in research and practice. The method is implemented as a tool in GRASS GIS which makes it available as a practical and flexible tool. Extensive validation and assessment of the method on the specific case of urban trees confirm that the method is a highly accurate alternative to modelling visual exposure from street view imagery (ρ = 0.96) but that data quality and viewshed parametrisation are essential for achieving accurate results. Thanks to parallel processing and effective implementation, the method is applicable for city-wide scale analysis with high-resolution data on commodity hardware (here illustrated on the case of Oslo, Norway). Therewith, the method has potential application in many areas including strategic tree planting, scenario modelling and urban ecosystem accounting, as well as ecosystem service research.