Enhancing ecotourism site suitability assessment using multi-criteria evaluation and NSGA-II

To ensure that ecotourism development remains sustainable, the best place for such activities should be chosen based on the ecological potential. This study attempts to identify suitable ecotourism sites by developing a quantitative geographic model using multi-criteria evaluation (MCE), optimized by a non-dominated sorting genetic algorithm (NSGA-II). Three criteria (physical, biological, and socio-economic features), 13 sub-criteria, and 33 indices were first collected from primary and secondary data sources. Then, MCE method was applied to find ecotourism suitable areas, in which two methods of fuzzy overlay and weighted linear combination (WLC) were used to overlay criteria maps. Finally, NSGA-II was used to optimize ecotourism zoning through defining three objectives, including minimizing the distance from the sub-criteria of natural attractions, vegetation, and historical-cultural sites. Results show the WLC method is better than the fuzzy method at combining different layers to determine suitable zones for ecotourism, through which more than 50% of the study area, about 28,000 hectares, was classified as suitable for ecotourism. Matching 85% of suitable areas obtained by NSGA-II with high and very high suitable classes obtained by WLC shows that combining the MCE method with NSGA-II provided a more suitable hybrid method for ecotourism site suitability evaluation. This study creates a valuable tool for those responsible for planning and carrying out ecotourism initiatives, allowing them to further assess and conduct ecotourism projects.