Content area
Landscape visual evaluation is a key method for assessing the value of visual landscape resources. This study aims to enhance the visual environment and sensory quality of urban landscapes by establishing standards for the visual comfort of urban natural landscapes. Using line-of-sight and multi-factor analysis algorithms, the method assesses spatial visibility and visual exposure of building clusters in the core urban areas of Harbin, identifying areas and viewpoints with high visual potential. Focusing on the viewpoints of landmark 3D models and the surrounding landscape’s visual environment, the study uses the city’s sky, greenery, and water features as key visual elements for evaluating the comfort of urban natural landscapes. By integrating GIS data, big data street-view photos, and image semantic recognition, spatial analysis algorithms extract both objective and subjective visual values at observation points, followed by mathematical modeling and quantitative analysis. The study explores the coupling relationship between objective physical visual values and subjective perceived visibility. The results show that 3D visual analysis effectively reveals the relationship between landmark buildings and surrounding landscapes, providing scientific support for urban planning and contributing to the development of a more distinctive and attractive urban space.
Details
Visual perception;
Urban environments;
Urban planning;
Big Data;
Algorithms;
Visual observation;
Discriminant analysis;
Topography;
Depth perception;
Comfort;
Line of sight;
Factor analysis;
Architecture;
Image processing;
Visual stimuli;
Dimensional analysis;
Urban areas;
Aesthetics;
Visual perception driven algorithms;
Vegetation;
Research methodology;
Remote sensing;
Sensory properties;
Three dimensional models;
Visibility;
Design;
Geographic information systems;
Mathematical models;
Cities
1 School of Geomatics and Urban Spatial Informatics, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;
2 Guangxi Zhuang Autonomous Region Institute of Cartography, Guangxi 530201, China