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生态学杂志 ›› 2021, Vol. 40 ›› Issue (10): 3304-3313.doi: 10.13292/j.1000-4890.202110.039

• 研究报告 • 上一篇    下一篇

基于灾害危险性评价的乐山大佛风景区游览路线

曾雅婕1,傅红1*,刘勇2,税玥3,胡铭真1,耿藤瑜1   

  1. 1四川大学建筑与环境学院, 成都 610065;2乐山大佛风景名胜区管理委员会, 四川乐山 614000;3中国科学院水利部成都山地灾害与环境研究所, 成都 610041)
  • 出版日期:2021-10-10 发布日期:2022-04-01

Tour routes of Leshan Giant Buddha scenic area based on hazard risk evaluation.

ZENG Ya-jie1, FU Hong1*, LIU Yong2, SHUI Yue3, HU Ming-zhen1, GENG Teng-yu1   

  1. (1College of Architecture and Environment, Sichuan University, Chengdu 610065, China; 2Management Committee of Leshan Giant Buddha Scenic Area, Leshan 614000, Sichuan, China; 3Chengdu Institute of Mountain Hazards and Environment, Ministry of Water Resources, Chinese Academy of Sciences, Chengdu 610041, China).
  • Online:2021-10-10 Published:2022-04-01

摘要: 灾害的频发严重威胁着风景区的游线畅通和游人安全。将灾害危险性评价融入风景区选线,对于制定减灾防灾战略以及优化风景区发展规划具有重要意义。本文以乐山大佛风景区为例,基于最小累积阻力模型,构建了地质灾害、洪水灾害、森林火灾以及生物灾害危险性综合评价下的灾害危险阻力面,以游览观赏点和景观资源点为源,利用GIS识别出了灾害影响下风景区游览路线的优化结果。结果表明:乐山大佛风景区主要受地质灾害和洪水灾害影响,灾害危险呈环状分布,中部高四周较低、北侧高东南侧低、滨水危险高于山地区域,整体危险性高;依据携程网旅游数据以及风景区总体规划的景源分布,确定源点51处;通过最小累积阻力计算获取风景区游览路线77条,总长34.322 km,结合遗产保护和实际利用需要,对选线结果进行优化,得到优化后路线63条。

关键词: 最小累积阻力模型, 灾害危险性指数, 游览路线, 选线优化

Abstract: The frequent occurrence of disasters seriously threatens the smooth route flow and visitor’s safety in scenic areas. The integration of hazard risk assessment into the route selection of scenic areas is important for the formulation of disaster mitigation and prevention strategies and the optimization of scenic area development planning. Based on the minimum cumulative resistance model, we constructed a disaster risk resistance surface under the comprehensive evaluation of geological disasters, flood disasters, forest fires, and biological disasters. With sightseeing spots and landscape resource points as sources, GIS was used to identify the optimization results of the sightseeing route of Leshan Giant Buddha Scenic Area under the influence of disasters. The results showed that Leshan Giant Buddha Scenic Area was mainly affected by geological and flood disasters. The disaster hazards were distributed in a circular pattern, with high disaster hazards in central area surrounded by low disaster hazards, high disaster hazards in north side and low disaster hazards in southeast side. Waterfront hazards were higher than that in mountainous areas, and the overall hazard was high. There were 51 source points being identified based on Ctrip.com tourism data and scenic source distribution of scenic area overall planning. We obtained 77 scenic area tour routes through minimum cumulative resistance calculation, with a total length of 34.322 km. Combined with heritage protection and actual utilization needs, the route selection results were optimized, resulting in 63 routes after optimization.

Key words: minimum cumulative resistance model, disaster risk index, tour route, route selection optimization.