A Campus Landscape Visual Evaluation Method Integrating PixScape and UAV Remote Sensing Images

Landscape, as an important component of environmental quality, is increasingly valued by scholars for its visual dimension. Unlike evaluating landscape visual quality through on-site observation or using digital photos, the landscape visualization modeling method supported by unmanned aerial vehicle (UAV) aerial photography, geographic information System (GIS), and PixScape has the advantage of systematically scanning landscape geographic space. The data acquisition is convenient and fast, and the resolution is high, providing a new attempt for landscape visualization analysis. In order to explore the application of visibility modeling based on high-resolution UAV remote sensing images in landscape visual evaluation, this study takes campus landscape as an example and uses high-resolution campus UAV remote sensing images as the basic data source to analyze the differences between the planar method and tangent method provided by PixScape 1.2 software in visual modeling. Six evaluation factors, including Naturalness (N), Normalized Shannon Diversity Index (S), Contagion (CONTAG), Shannon depth (SD), Depth Line (DL), and Skyline (SL), are selected to evaluate the landscape vision of four viewpoints in the campus based on analytic hierarchy process (AHP) method. The results indicate that the tangent method considers the visual impact of the vertical amplitude and the distance between landscape and viewpoints, which is more in line with the real visual perception of the human eyes. In addition, objective quantitative evaluation metrics based on visibility modeling can reflect the visual differences of landscapes from different viewpoints and have good applicability in campus landscape visual evaluation. It is expected that this research can enrich the method system of landscape visual evaluation and provide technical references for it.

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