Spatial Differentiation, Influencing Factors, and Development Paths of Rural Tourism Resources in Guangdong Province

Abstract

Rural tourism resources are the core carriers of rural tourism. It is, therefore, beneficial to further optimize the layout of rural tourism and to explore the spatial differentiation of rural tourism resources and their influencing factors. Taking 4670 rural tourism resources in Guangdong Province in China as the research object, this study explores the spatial distribution patterns of rural tourism resources through the nearest neighbor index, grid dimension analysis, kernel density analysis, and standard deviation ellipse method. Geodetectors are used to identify the influencing factors of the spatial heterogeneity of these resources in Guangdong Province. The findings reveal the following: (1) The distribution of rural tourism resources in Guangdong Province shows a tendency of agglomeration along the Tropic of Cancer, and the spatial distribution is unbalanced. The hot and cold spots show a “northeast-southwest” distribution trend. Furthermore, most of the hotspots form three high-density core areas, the sub-dense stretch zones connect into a w-shaped belt, and the sub-cold areas and sub-hot areas show a large expansion trend, thus forming five radiation areas. (2) The distribution of rural tourism resources in Guangdong Province is affected by multiple factors. In particular, the force of agricultural resource endowment, tourism resource endowment and transportation location are relatively strong, and social economy and tourist source market are the weak factors.

Spatial distribution and suitability evaluation of nighttime tourism in Kunming utilizing multi-source data

“…For instance, Li et al applied POI data to explore the spillover effect of tourism space [ 13 ]. Meanwhile, Liao et al explored the spatial differentiation of rural tourism resources and its influencing factors through rural POI data [ 14 ]. Nonetheless, the application of such data in nighttime tourism research remains limited having only been applied to explore the relationship between tourism POI and nighttime lighting [ 15 ] and that between tourism economy and nighttime lighting [ 16 ].…”

Prediction model and demonstration of regional agricultural carbon emissions based on Isomap–ACO–ET: a case study of Guangdong Province, China

“…In addition, the agricultural planting structure should be optimized, and crops such as southern subtropical fruits, vegetables and flowers with Guangdong characteristics and competitive advantages should be developed according to local conditions, so as to build an industrial belt of advantageous agricultural products and improve the quality and efficiency of agricultural products 37 . Once again, leisure tourism and eco-tourism agriculture should be developed to promote the improvement of the rural ecological environment in order to ensure the healthy and sustainable development of the agricultural ecology of Guangdong Province 38 .…”

Effects of local policies and public goods on tourism in rural areas: Exploring spatial dependence patterns

“…Another source of public goods in rural areas is related to cultural heritage. Cultural tourism attractions have shown agglomeration effects and clustering for tourism in rural areas using the spatial approach (Liao et al, 2022;Zhao et al, 2022). Álvarez-Díaz et al (2017), using the Spatial Autoregressive (SAR) model and a gravity model, showed that attractive public goods had positive and significant effects on the number of tourist trips in Spanish regions.…”