Evaluation of rural tourism land competitiveness based on neural-network method and weighted model: a case study of Miyun District in Beijing, China

doi:10.3969/j.issn.1004-1524.2021.08.19

Acta Agriculturae Zhejiangensis ›› 2021, Vol. 33 ›› Issue (8): 1519-1528.DOI: 10.3969/j.issn.1004-1524.2021.08.19

• Agricultural Economy and Development • Previous Articles Next Articles

Evaluation of rural tourism land competitiveness based on neural-network method and weighted model: a case study of Miyun District in Beijing, China

XIAN Weixuan¹^,²(), SHANG Guobei², LIU Qiaoqin³, LIU Yu¹^,^*()

1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China
2. School of Land Science and Space Planning, Hebei University of Geology, Shijiazhuang 050031, China
3. College of Ecology and Environment, Institute of Disaster Prevention, Sanhe 065201, China

Received:2020-11-27 Online:2021-08-25 Published:2021-08-27
Contact: LIU Yu

Abstract

Abstract:

Scientific evaluation of the competitiveness of rural tourism land and identification of its obstacles are the premise and basis for optimizing the layout of rural tourism industry, and also an effective way to achieve rural revitalization.In the present study, Miyun District of Beijing was selected as an sample. Thirteen indicators from three dimensions of resource endowment characteristics, regional ecological environment and tourism development conditions were selected to construct a tourism land competitiveness evaluation model based on neural-network method, which would help reveal the pattern of rural tourism land competitiveness in Miyun District. The diagnostic model of obstacle factors was introduced to analyze limiting factors of the competitiveness types of main rural tourism land. The results were shown as follows. (1) Low-competitiveness rural tourism land was distributed in clusters in the south of Miyun District and northeast of Miyun Reservoir. Medium-competitiveness rural tourism land was distributed along Chao River Axis Zone, Bai River Axis Zone, Andamu River Axis Zone and northern mountainous belt, with 176 units in Xin’anzhuang and Fenggezhuang Village and so on. High competitiveness rural tourism land was in the form of dots, covering the villages of Zhangjiafen, Simatai, Jiayu, Hebei, Shicheng, Shengshuitou, Shimayu and Longtangou. (2) The medium competitiveness region was divided into the resource, environment and development obstacle types based on main obstacle factors, and corresponding optimization countermeasures were put forward, respectively. The results could provide references for rural industrial land planning.

Key words: multisource data, neural-network method, diagnostic model of obstacle factors, rural tourism land

CLC Number:

S-9
F304.5

XIAN Weixuan, SHANG Guobei, LIU Qiaoqin, LIU Yu. Evaluation of rural tourism land competitiveness based on neural-network method and weighted model: a case study of Miyun District in Beijing, China[J]. Acta Agriculturae Zhejiangensis, 2021, 33(8): 1519-1528.

Figures/Tables 4

References 24

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维度 Dimension	指标 Index	权重 Weight
资源禀赋特征	休闲旅游资源个数Number of leisure resources	0.064
Characteristics of resource endowment	休闲旅游资源丰度Abundance of leisure resources	0.174
	评价单元知名度Evaluation unit popularity	0.028
	旅游用地禀赋指数Tourism land endowment index	0.100
区域生态环境Regional ecological environment	地形位指数Topographical index	0.003
	植被覆盖度Vegetation coverage	0.087
	生态用地比例Proportion of ecological land	0.010
旅游开发条件Tourism development conditions	村域公路里程Mileage of village road	0.095
	自驾可达便利度Self driving accessibility	0.116
	骑行可达便利度Riding accessibility	0.058
	距区中心远近程度Distance to the center of the zone	0.151
	便民设施完善程度Improvement of convenience facilities	0.019
	政策优势Policy advantages	0.096

维度 Dimension	指标 Index	权重 Weight
资源禀赋特征	休闲旅游资源个数Number of leisure resources	0.064
Characteristics of resource endowment	休闲旅游资源丰度Abundance of leisure resources	0.174
	评价单元知名度Evaluation unit popularity	0.028
	旅游用地禀赋指数Tourism land endowment index	0.100
区域生态环境Regional ecological environment	地形位指数Topographical index	0.003
	植被覆盖度Vegetation coverage	0.087
	生态用地比例Proportion of ecological land	0.010
旅游开发条件Tourism development conditions	村域公路里程Mileage of village road	0.095
	自驾可达便利度Self driving accessibility	0.116
	骑行可达便利度Riding accessibility	0.058
	距区中心远近程度Distance to the center of the zone	0.151
	便民设施完善程度Improvement of convenience facilities	0.019
	政策优势Policy advantages	0.096

Evaluation of rural tourism land competitiveness based on neural-network method and weighted model: a case study of Miyun District in Beijing, China

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