[H-CG19] International comparison of landscape appreciation and recreation

[HCG19-P04] Establishing Landscape networks Based on Visual Quality and Ecological Resistance: A case study in Tianmeng Scenic Spot, China

*MENGLIN XU¹, Hajime Matsushima² (1.Graduate School of Agriculture, Hokkaido Univ., 2.Research Faculty of Agriculture, Hokkaido Univ.)

Keywords:Landscape visual sensitivity, Ecological resistance, Landscape pattern, The minimum cumulative resistance (MCR) model, Tianmeng mountain

Forest-based scenic spot has received widespread attention for its landscape aesthetics and ecological values, but the rapid growth of tourism activities and landscape exploitation make it challenging to balance human recreational needs, landscape quality and ecological stability. This study aimed to evaluate, quantitative and grade the landscape quality from subjective human aesthetic needs and objective landscape visual sensitivity. After the selection of high-quality landscape viewpoints as sources, the minimum cumulative resistance (MCR) model was used to screen the optimal paths for connectivity among viewpoints with consideration of ecological resistance. High-quality landscape viewpoints, optimal paths and ecological resistance surfaces constructed the landscape network for sustainable development. The results showed that the landscape quality of viewpoints in Tianmeng scenic spot was not good, only 32.4% of them had both good performance of landscape aesthetics and landscape visual sensitivity; In the analysis of ecological resistance surfaces, the proportion of very-high resistance areas and high resistance areas were 32.9%, which were mostly distributed in the main tourism roads and their buffer areas around the northwest of Tianmeng Mountain. 11 landscape core viewpoints and 6 secondary viewpoints, all with high landscape aesthetics, were selected as high-quality visual landscape, and then based on the ecological resistance surfaces, 11 core landscape dissemination paths and 6 secondary landscape dissemination paths were identified respectively using MCR model. The method could provide scientific decision support to enhance the effectiveness of viewpoints as well as sustainable landscape planning for development.