Assessment of Visual Qualities, Impacts, and Behaviours, in the Landscape, by Using Measures of Visibility

The application of information technology to landscape analysis dates back to the early work in computer-based mapping. Indeed, much of the early development of what became geographic information systems (GIS) and three-dimensional landscape simulation was undertaken by landscape architects. Mapping of viewsheds quickly became a key element of the landscape-planning process. The process was applied to determination of both view characteristics and potential visual impacts. The algorithms for viewshed analysis were incorporated into GIS products at an early stage in their evolution, but have evolved very little since despite the identification of significant potential enhancements. Extension of the simple binary mapping of GIS has therefore depended on specific developments by individual researchers. These GIS extensions have generated models of visual quality and visual impact using mapped variables. More recently it has become apparent that the essentially two-dimensional approach to view analysis afforded by GIS is inadequate in situations with strong three-dimensional elements. The upsurge in agent-based modeling has demanded a new standard in computer-based visual interpretation of landscape. Both the historic role of GIS-based visual modeling and the potential of 3D-based visual modeling are reviewed.

[1]  Fabio Gagliardi Cozman,et al.  Depth from scattering , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[2]  Cities from the sky photogrammetric modeling of CyberCity is coming of age , 2002 .

[3]  Terry C. Daniel,et al.  The effects of atmospheric optical conditions on perceived scenic beauty , 1981 .

[4]  Nicholas C. Coops,et al.  Procedures for predicting habitat and structural attributes in eucalypt forests using high spatial resolution remotely sensed imagery , 1998 .

[5]  Gregory J. Buhyoff,et al.  Distance and Scenic Beauty , 1983 .

[6]  Susan M. Larson.  Future directions and challenges for quantitative environmental visualization , 1992 .

[7]  Wayne D. Iverson,et al.  VIEWIT: computation of seen areas, slope, and aspect for land-use planning , 1975 .

[8]  Ian D. Bishop,et al.  VISUAL THRESHOLDS FOR DETECTION, RECOGNITION AND VISUAL IMPACT IN LANDSCAPE SETTINGS , 2000 .

[9]  H. R. Gimblett,et al.  Intelligent recreation agents in a virtual GIS world , 2000 .

[10]  Peter F. Fisher,et al.  Extending the applicability of viewsheds in landscape planning , 1996 .

[11]  M. Germino,et al.  Estimating visual properties of Rocky Mountain landscapes using GIS , 2001 .

[12]  Ian D. Bishop,et al.  Prediction of scenic beauty using mapped data and geographic information systems , 1994 .

[13]  Ian D. Bishop,et al.  Comparing regression and neural net based approaches to modelling of scenic beauty , 1996 .

[14]  Leila De Floriani,et al.  Visibility Algorithms on Triangulated Digital Terrain Models , 1994, Int. J. Geogr. Inf. Sci..

[15]  E. Shafer,et al.  How to measure preferences for photographs of natural landscapes , 1977 .

[16]  Randy Gimblett,et al.  Spatially-explicit autonomous agents for modelling recreation use in complex wilderness landscapes , 1996 .

[17]  David Miller,et al.  A method for estimating changes in the visibility of land cover , 2001 .

[18]  Ian D. Bishop,et al.  Automated mapping of visual impacts in utility corridors , 1988 .

[19]  Carl Steinitz,et al.  Toward a sustainable landscape with high visual preference and high ecological integrity: the loop road in Acadia National Park, U.S.A. , 1990 .

[20]  Markus H. Gross,et al.  The analysis of visibility - Environmental interactions between computer graphics, physics, and physiology , 1991, Comput. Graph..

[21]  Ian D. Bishop.  Testing perceived landscape colour difference using the Internet , 1997 .

[22]  Ian D. Bishop,et al.  Determination of Thresholds of Visual Impact: The Case of Wind Turbines , 2002 .

[23]  Stephen Kaplan,et al.  Perception and landscape: Conceptions and misconceptions. , 1979 .

[24]  Ian D. Bishop,et al.  Predicting movement choices in virtual environments , 2001 .

[25]  Daniel Thalmann,et al.  A paradigm for controlling virtual humans in urban environment simulations , 2000, Appl. Artif. Intell..

[26]  Ian D. Bishop,et al.  Using Image Depth Variables as Predictors of Visual Quality , 2000 .

[27]  M. Benedikt,et al.  To Take Hold of Space: Isovists and Isovist Fields , 1979 .