Neil Sang

Analysing Visual Landscape Complexity: Theory and Application

Abstract The experience of landscape has, through the development of the European Landscape Convention, been highlighted as an important aspect to be incorporated in the management and planning of future landscapes. Complexity is a concept that appears in the development of indicators for several landscape functions, including visual quality and biodiversity. In environmental psychology, complexity has been used as an explanatory factor for landscape preference. This paper outlines the factors which constitute the dimensions of complexity perception and how these relate to coherence—a factor which seems to interact with complexity as regards to landscape experience. The paper further explores how indicators of landscape complexity developed within the framework of landscape ecology may be applied and used to capture relevant information on visually experienced landscape complexity. Particular attention is paid to the dimensional transitions which must be considered in order for map based indicators and perceived environmental qualities to be readily related in an applied setting. The paper concludes with some suggested models for how to link landscape indicators with landscape preference in future research.

Landscape Metrics and Visual Topology in the Analysis of Landscape Preference

Recognition of the value of landscapes, environmentally, economically, and to quality of life—and, importantly, the embedding of these concepts in legislation such as the European Landscape Convention—has led to the need for an ‘objective’ assessment of these values and the potential impact of changes to them. But studies relating preference information to metric analysis of planimetric viewsheds have so far provided only limited explanation of preference. It has been suggested that this is due to the effect of perspective on the visual topology of the view generating different metrics in perspective from those on the flat map. The completion of the Pan European Study under the EU Framework 5 Visulands project provided a large sample of preference responses to a limited number of computer-generated simple landscape scenarios. As such this is an ideal opportunity to test the significance of perspective on metric correlation with preference. This paper considers the degree to which metrics are altered by a panoramic or viewshed analysis, and the significance of this for any correlation with the preference scores. The implications for the role of the respective media in planning are considered, including that of 3D visualisation as a means for eliciting opinion on landscape preference.

Wild Vistas: Progress in Computational Approaches to ‘Viewshed’ Analysis

Understanding the potential visual impact of landscape change provides the opportunity to both prevent inappropriate change and minimize the impact of necessary service provision. Wilderness areas are, by definition, particularly sensitive to the visible presence of human activity and built structures. As GIS technology has reached disciplines with a specific aesthetic interest in landscape the visual questions posed of data have become more demanding. This may be a matter of the degree of confidence which may be placed on the results of visibility analysis given data uncertainties and vague definitions. Alternatively it may be that more qualitatively subtle questions are to be addressed, concerning not just whether a location is visible, but how prominent it is in the view or indeed how notable it is psychologically. In some cases relevant techniques have existed for decades, but their significance is only now being appreciated. Other aspects are stimulating renewed interest at the research front that bring together disciplines from GIS, computer graphics, landscape planning and psychology. This chapter considers the evolution of the questions being asked of visual analysis as well as techniques and technologies developed to answer them.

The Euler character: a new type of visual landscape metric?

Landscape-preference theories such as prospect-refuge theory and Kaplan and Kaplans landscape-preference matrix and theories of visual perception propose that the physical structure of the landscape has a direct psychological effect on people due to evolved sensitivity to particular defining characteristics. Efforts to identify consistent quantitative relationships between metrics of these characteristics and human preference have had some success. However, the field has also faced some criticisms due to low explanatory power in the results reducing confidence that relationships found can be applied to other contexts. In this paper we argue that dependence on generalised planar maps for the derivation of the metrics but on viewpoint-specific perspective photographs for the preference data is a potential cause of low explanatory power. How viewpoint change may affect scene characteristics needs to be better understood if representative viewpoints are to be chosen to allow results which are general to an area, in particular the difference between discreet (topological) changes and continuous changes. This paper presents the results of an experiment to test whether the topological complexity of a view, as measured by the Euler character of the horizon graph, has perceptual significance. We investigate if images with higher horizon-graph complexity were considered more interesting than those with lower graph complexity via a forced-choice Internet survey.

The topological viewshed: embedding topological pointers into digital terrain models to improve GIS capability for visual landscape analysis

ABSTRACT The effort to develop a Digital Earth has made dramatic progress in terms of visualisation and visual data integration for use-cases which demand semantically rich analysis. To provide this analysis and ensure legitimate representations of the spatial data from which visualisation are derived, it is necessary to provide more comprehensive analytical capabilities of the view. Questions of aesthetic valuation of landscape require a richer analytical response than simply ‘whether and possibly how much of’ an object or area of land can be seen. It requires interrogation of the scene as it appears and to distinguish between transient visual effects and those locally invariant to view point change. This paper explores a data structure to support scene analytics. As such, it first reviews the existing techniques from the fields of GIS and computer graphics as to their potential and limitations in providing a qualitatively more nuanced visual analysis. It then introduces a new method of encoding visually apparent relationships into terrain models. A prototype implementation is presented based on the Quad-Edge Triangular Irregular Network, though it is believed that raster or vector implementation would be possible. Although developed primarily with landscape analysis in mind, the method could have wider applicability.