Spatial Structure and Development of Tourism Resources based on Point Pattern Analysis: A Case Study in Hainan Island, China

doi:10.5814/j.issn.1674-764x.2022.06.011

Abstract

Abstract:

Tourism resources are the basic materials of tourism development, and they also provide the support for regional tourism spatial competition. The development of tourism depends on the degree to which tourism resources are utilized, and it is of great guiding significance for their development and utilization to study their spatial structure. Based on a large sample of data on tourism resources, and starting from the characteristics of multi-type, multi-level and multi-combination, this paper puts forward a framework and method for analyzing the spatial structure of tourism resources. Taking Hainan Island as an example, this paper describes the spatial structure of tourism resources in Hainan Island by using the method of point pattern analysis, identifies the tourism resource development zones, and puts forward some suggestions for the development of tourism resources. The results are as follows: (1) The characteristic scale of the spatial structure of tourism resources in Hainan Island is 30.5 km, and there are significant differences in the distributions of all kinds of tourism resources. (2) Through the spatial structure map of tourism resources, the tourism resource development zones are identified, including three tourist central city levels, “one horizontal and three vertical” tourist belts and four tourist combination areas. (3) By combing the distribution of tourism resources and the development zones in Hainan Island, the cross-border characteristics of the tourism resources and development zones are obvious. In order to give full play to the spatial combination and superposition effect of tourism resources, a change from a single isolated development mode to the overall combined development between regions is suggested. On the provincial scale, it is relatively accurate to describe the spatial structure of tourism resources for point data with a large sample size. However, the method of point pattern analysis can not only accurately describe the spatial structure of tourism resources, but it can also provide reference for other types of regional spatial analyses. The research results provide a scientific basis for the spatial planning of regional tourism resources and have practical significance for the development of regional tourism.

Key words: tourism resources, spatial structure, development area, point pattern analysis method, Hainan Island, China

ZHANG Tongyan, WANG Yingjie, WANG Yingying, ZHANG Shengrui, YU Hu. Spatial Structure and Development of Tourism Resources based on Point Pattern Analysis: A Case Study in Hainan Island, China[J]. Journal of Resources and Ecology, 2022, 13(6): 1058-1073.

Figures/Tables 14

Fig. 1 Location map and administrative subdivisions of Hainan Island

Fig. 2 Spatial location of tourism resource points within the large sample size for Hainan Island

Table 1 Classification of physical tourism resources on Hainan Island

Primary type	Main type	Number of tourism resources
Natural tourism resource	Geographical landscapes	1640
	Water landscapes	1591
	Biological landscapes	253
	Astronomical phenomena and meteorological landscapes	32
	Ocean and coastal landscapes	180
Humanistic tourism resource	Buildings and facilities	4850
Humanistic tourism resource	Ruins and remains	1042

Table 2 Evaluation grades of tourism resources

Score Interval	Grade of tourism resources
≥90	Level five
75-89	Level four
60-74	Level three
45-59	Level two
30-44	Level one

Fig. 3 Spatial composition of (a) humanistic tourism resources, (b) natural tourism resources, and (c) combination of humanistic and natural tourism resources. Note: The abbreviations such as GW in the figure are the combination of acronyms of different main type of tourism resources.

Fig. 4 Model flowchart for analyzing the spatial structure and development of tourism resources

Fig. 5 L-function analysis of tourism resources Note: d curve is Expected—Random spatial pattern; L(d) curve is Observed—Spatial patterns; LwConfEnv is lower confidence interval; HiConfEnv is higher confidence interval.

Fig. 6 Kernel density maps of (a) natural tourism resources, and (b) humanistic tourism resources.

Fig. 7 (a) Center of Kernel density map, and (b) grade classification of center of Kernel density map of the main types of tourism resources.

Fig. 8 Numbers of spatial combinations among the main types of tourism resources

Fig. 9 Spatial combinations of (a) natural, (b) humanistic, and (c) natural and humanistic tourism resources.

Fig. 10 Distribution pattern of tourism resource hotspots on Hainnan Island

Fig. 11 Distribution pattern of the tourism resource belts on Hainan Island

Fig. 12 Distribution pattern of tourism resource combined areas on Hainan Island

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