Development and application of 3D spatial metrics using point clouds for landscape visual quality assessment

Abstract

Landscape visual quality (LVQ) relates to a landscape's spatial, functional and visual structure at a given time, which can affect the senses and experience of the person using or viewing the landscape. A holistic LVQ assessment can be undertaken by using two complementary approaches. The first uses visual quality assessment tools to measure a person's perceptive responses to landscapes; the second, the focus of our study, is based on the quantitative assessment of the physical attributes of landscapes. The physical attributes of landscapes refer to their spatial configuration and composition, and have conventionally been characterised using 2D or 2.5D metrics. The use of 3D attributes is an emerging field, but there is scant information on the range of 3D metrics that can describe the physical attributes of landscapes and which relate to the perception of landscape quality. This study develops 3D spatial metrics to describe landscapes' structures and spatial characteristics grounded on landscape visualization theory. These metrics are derived from point clouds and describe 3D attributes of volume and area, landscape diversity, shape, connectivity, colour, topography, and openness. The effectiveness of the 3D spatial metrics to quantify LVQ was verified using a set of urban landscapes in the high-rise, compact environment of our study sites. The results show that 3D spatial metrics can successfully detect the differences among landscapes in the dimensions of naturalness, complexity, coherence and visual scale. For example, landscapes with a random distribution and irregular shapes had high values in horizontal, vertical, and distance diversity (HVDD) and the shape index, respectively, indicating their high spatial and shape diversities. Our study highlights the potential of using 3D spatial metrics derived from point clouds for a more holistic and objective LVQ assessment.