Spatial Potential of Recreational Services in Western Hubei Region in Light of the “All-for-One Tourism” Development—A Machine Learning Approach Based on Ensemble Model

Abstract

Under the call for “all-for-one tourism” development, the focus of regional-scale recreational services is shifting from the construction of individual scenic spots and tourist areas towards the comprehensive planning of tourist destinations, so as to propel China’s rural revitalization and regional coordinated development. In research and practice, however, it is still challenging to identity and evaluate spatial locations for developing tourism according their cultural and environmental resource and characteristics and prioritizing the high-potential ones. Employing the whole western Hubei region as a case study, this paper proposes a method of assessing recreation potential within the research framework on cultural ecosystem services, and uses multi-sourced social-ecological data to develop an SDM model via ensemble machine learning. Through analyses of the environmental features of 336 recreational hotspots in the study area, the model predicts the areas with high recreation potential in continuous areas. This study intends to establish a technique path to examine the regional-scale pattern of recreational spaces via numerical analysis of environmental features, and to provide a reference for relevant spatial development strategies of all-for-one tourism and rural revitalization.