Abstract
Human interactions with ecosystems primarily occur at a perceptible spatial scale, where visual landscape quality serves as a crucial link between human perception and ecological functions. Although research in environmental psychology and landscape ecology suggests that visual and ecological quality are often correlated through spatial characteristics, their systematic integration remains limited, largely due to disciplinary boundaries and methodological constraints. Visual landscape studies emphasize human perceptual and aesthetic values, often using qualitative assessments, while landscape ecology focuses on ecosystem processes and spatial patterns, typically relying on quantitative analysis. To bridge the above divide, this study conducts a systematic review and meta-analysis to explore shared spatial characteristics, defined as the composition and configuration of landscape elements, that underpin both perspectives. Four common spatial dimensions emerged: naturalness, spaciousness, coherence, and complexity. These abstract dimensions were further translated into measurable landscape metrics, capturing spatial patterns relevant to both ecological function and visual perception. Moreover, a set of spatial metrics collectively address both horizontal and vertical perspectives of landscape structure, encompassing indicators that reflect ecological integrity and visual quality across spatial planes. This research offers a promising framework for understanding shared spatial characteristics and evaluating spatial metrics that concurrently support biodiversity conservation and the maintenance of visually appealing landscapes, thereby fostering harmonious coexistence between humans and wildlife.
| Original language | English |
|---|---|
| Article number | 129007 |
| Journal | Urban Forestry and Urban Greening |
| Volume | 112 |
| DOIs | |
| State | Published - Oct 2025 |
| Externally published | Yes |
Keywords
- Composition and configuration
- Landscape ecology
- Spatial characteristics
- Systematic review
- Visual landscape
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