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地理研究    2018, Vol. 37 Issue (12): 2517-2527     DOI: 10.11821/dlyj201812012
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
基于RM的福建省旅游扶贫重点村生态脆弱性风险评价
林明水1,2(),林金煌2,3,王开泳2(),陈田2,伍世代1
1. 福建师范大学旅游学院, 福州 350117
2. 中国科学院地理科学与资源研究所, 北京 100101
3.福建师范大学地理科学学院, 福州 350117
Evaluation of sustainable tourism for eliminating poverty in key villages based on risk matrix method: A case study of Fujian province
LIN Mingshui1,2(),LIN Jinhuang2,3,WANG Kaiyong2(),CHEN Tian2,WU Shidai1
1. College of Tourism, Fujian Normal University, Fuzhou 350117, China
2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
3. College of Geographic Science, Fujian Normal University, Fuzhou 350117, China
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摘要 

贫困山区的生态环境较为脆弱,科学地评价扶贫村生态脆弱性风险是保障可持续旅游扶贫的重要前提。以南方红壤丘陵山地生态脆弱区福建省472个旅游扶贫重点村为例,基于风险矩阵法和GIS空间分析法构建重点村生态脆弱性风险矩阵,将重点村生态脆弱性风险划分为五个等级,并提出相应的可持续旅游扶贫的路径与建议。研究发现:重点村生态脆弱性风险的潜在影响程度主要驱动因子是人为因素,自然因素是次要驱动因子;基于风险矩阵法构建的生态脆弱性风险矩阵可以有效地评价重点村生态脆弱性风险等级,进一步验证了“概率—损失”模型的可行性;福建省472个重点村中,64.83%重点村处于生态脆弱性风险等级较高的区域,仅有166个重点村现有的旅游扶贫模式是可持续的。可持续旅游扶贫形势严峻,必须因地制宜地开展旅游扶贫与生态保育。

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林明水
林金煌
王开泳
陈田
伍世代
关键词 生态脆弱性风险可持续旅游扶贫风险矩阵法SPCA福建 
Abstract

The eco-environment of rural poverty-stricken areas is so fragile to make the relationship between poverty and eco-environment multidimensional, complex and different. Governments, academia and industry have reached a consensus on the importance of avoiding poverty alleviation villages' falling into "poverty trap" and developing tourism and other green industries to get rid of poverty. However, how to maintain the balance between socio-economic development and ecological protection in poor areas has been a hot and tough issue in the research of tourism poverty alleviation. The effective evaluation of the risk of ecological vulnerability in poverty alleviation villages has become the basis and important premise of developing sustainable tourism for eliminating poverty. Therefore, this paper established a risk matrix of ecological vulnerability in key villages based on risk matrix method and GIS spatial analysis method. A survey of 472 key rural poverty alleviation villages in Fujian province was conducted and some data were collected. These key villages were classified into five categories according to the risk level of ecological vulnerability: very high, high, medium, low and very low. This paper also put forward the corresponding countermeasures and suggestions for sustainable tourism poverty alleviation. We identified 7 main driving factors that lead to the risk of ecological vulnerability, among which human factors have gradually replaced the natural factors to become the main leading factors. SPCA analysis shows that there are 4 man-made factors with a cumulative contribution rate (CCR) of 59.21%, while there are 3 natural factors with CCR of only 28.32%. What's more, constructing ecological vulnerability risk matrix can effectively evaluate the sustainability of tourism poverty alleviation in key villages. Some 64.83% of the 472 key villages in Fujian province are at high risk level. In terms of existing tourism poverty alleviation model, only 166 villages are sustainable, while 306 key villages should be changed or improved. This study deepened the theoretical research on sustainable tourism poverty alleviation in the red soil mountainous areas of southern China, and provided the experience for Fujian and even the country's fragile ecosystem to alleviate poverty.

Key wordsecological vulnerability risk    sustainable tourism for poverty alleviation    risk matrix method    SPCA    Fujian
收稿日期: 2018-06-12      出版日期: 2018-12-24
基金资助:中国博士后科学基金项目(2017M610976);福建师范大学社科高级别课题培育项目(VV-1810)
引用本文:   
林明水, 林金煌, 王开泳等 . 基于RM的福建省旅游扶贫重点村生态脆弱性风险评价[J]. 地理研究, 2018, 37(12): 2517-2527.
LIN Mingshui, LIN Jinhuang, WANG Kaiyong et al . Evaluation of sustainable tourism for eliminating poverty in key villages based on risk matrix method: A case study of Fujian province[J]. GEOGRAPHICAL RESEARCH, 2018, 37(12): 2517-2527.
链接本文:  
http://www.dlyj.ac.cn/CN/10.11821/dlyj201812012      或      http://www.dlyj.ac.cn/CN/Y2018/V37/I12/2517
Fig. 1  福建省乡村旅游扶贫重点村分布图
指标 计算方法及说明 数据来源
坡度() 数字高程模型(DEM)计算提取 DEM
高程 (m) 数字高程模型(DEM)计算提取 DEM
归一化植被指数NDVI NDVI=(Rnir-Rred)/(Rnir+Rred) Landsat 影像数据
多年平均降水量(mm) 多年降水点数据反距离加权(Kriging)插值 福建省气象局
www.fjqx.gov.cn
土壤侵蚀强度 福建省110万土壤侵蚀等级数据 国家地球系统科学数据
共享平台www.geodata.cn
旅游投资总额(万元) 全年旅游要素投资总额 原国家旅游局
www.cnta.gov.cn
贫困人口数(人) 各村建档贫困人口数量 原国家旅游局
www.cnta.gov.cn
餐饮和床位数量(个) “农家乐”餐位数,民宿和客栈床位数 原国家旅游局
www.cnta.gov.cn
休闲农业园面积(hm2 各村休闲农业园区数量与面积 原国家旅游局
www.cnta.gov.cn
旅游基础设施状况 各村游客服务中心、旅游厕所、停车场、垃圾处理设施、污水处理设施数量、村内道路是否硬化、是否有标识导览等 原国家旅游局
www.cnta.gov.cn
Tab. 1  指标描述及数据来源
指标 标准化赋值
2 4 6 8 10
坡度Slope( <5 5~15 15~25 25~35 >35
高程(m) <200 200~400 400~600 600~800 >800
归一化植被指数NDVI >0.8 0.6~0.8 0.4~0.6 0.2~0.4 <0.2
多年平均降水量(mm) >1750 1750~1600 1600~1450 1450~1300 <1300
土壤侵蚀强度 微度 轻度 中度 强烈 极强烈
旅游投资总额(万元) <50 50~100 100~150 150~200 >200
贫困人口数(人) <50 50~100 100~150 150~200 >200
餐饮和床位数(个) <50 50~100 100~150 150~200 >200
休闲农业园面积(hm2 <500 500~1000 1000~1500 1500~2000 >2000
旅游基础设施状况 非常完善 较完善 完善 不完善 非常不完善
Tab. 2  分等级赋值标准
脆弱性 等级标准 生态特征
微度脆弱 0~3 重点村生态系统结构和功能合理完善,所承受压力小,生态系统稳定,抗旅游活动干扰能力和自我恢复能力强
轻度脆弱 3~5 重点村生态系统结构和功能较为完整,所承受压力较小,生态系统较稳定,抗旅游活动干扰能力和自我恢复能力较强
中度脆弱 5~6 重点村生态系统结构和功能尚可维持,所承受压力接近生态阈值,生态系统较不稳定,对旅游活动干扰较为敏感,自我恢复能力较弱
重度脆弱 6~8 重点村生态系统结构和功能出现缺陷,所承受压力大,生态系统不稳定,对旅游活动干扰敏感性强,受损后恢复难度大
极度脆弱 8~10 重点村生态系统结构和功能严重退化,所承受压力极大,生态系统极不稳定,对旅游活动干扰极度敏感,受损后恢复难度极大,甚至不可逆转
Tab. 3  生态脆弱性分级标准
风险的发生概率 说明 等级标准
非常低 基本不可能发生 [0,1.5)
较低 极少发生 [1.5,3)
一般 偶尔发生 [3,4.5)
较高 可能发生 [4.5,6)
非常高 很有可能发生 [6,10)
Tab. 4  生态脆弱性风险的发生概率说明
风险的
发生概率
风险的潜在影响程度
微度脆弱 轻度脆弱 中度脆弱 重度脆弱 极度脆弱
非常低 很低 很低
较低 很低
一般
较高 很高
非常高 很高 很高
Tab. 5  生态脆弱性风险等级对照表
Fig. 2  重点村生态脆弱性等级空间分布
风险的发生概率 福州市 宁德市 莆田市 漳州市 泉州市 龙岩市 三明市 南平市 合计(个/%)
非常低 9 5 2 3 2 10 12 5 48/10.17
较低 4 17 2 4 4 11 18 7 67/14.19
一般 12 28 3 7 9 15 28 12 114/24.15
较高 5 46 4 11 12 19 43 17 157/33.26
非常高 2 21 4 13 6 12 21 7 86/18.23
合计(个/%) 32/6.78 117/24.79 15/3.18 38/8.05 33/7.00 67/14.19 122/25.85 48/10.16 472/100
Tab. 6  重点村生态脆弱性风险的发生概率统计表
Fig. 3  重点村生态脆弱性风险等级空间分布
Fig. 4  重点村生态脆弱性风险等级空间核密度
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