Utilizing multi-criteria decision to determine the best location for the ecotourism in the east and central of Fars province, Iran

Abstract

To reduce the negative effects of tourism on the environment, the importance of ecotourism is increasingly considered because this form of tourism helps to protect the environment and sustainable development of an area. So, it is important to determine suitable places for tourism to better manage the study area. The aim of this study is to identify potential ecotourism sites using ordered weight averaging (OWA) and fuzzy quantifier algorithms in the east and central of Fars province, Iran. Required spatial data such as geology, soil, slope land, topographic roughness index (TRI), vegetation, surface water, elevation, protected area, climate, distance to road, and distance to the village were utilized. To prepare ecotourism maps with different confidence levels, eleven ordered weights were applied corresponding to the eleven parameters that were rank-ordered for each parameter after the modified factor weights were applied. Also, the feature selection algorithm (random search and genetic search methods) was used to select the most important parameters to determine the ecotourism map. The results showed that, with decreasing risk (α = 0), almost all of the study area was unsuitable for ecotourism while, with increasing risk (α = 20), all of the study areas were suitable for ecotourism. One of the ecotourism maps prepared with different confidence levels can be suggested based on the different conditions of tourists so that, if the tourist has a limited time, ecotourism maps with a higher degree of confidence levels are recommended and vice versa. This is one of the innovations of the present research. Also, the results of the random search method with the least error show that slope, elevation, climate, distance to river, and distance to road parameters are the most important parameters in preparing the ecotourism map of the region. So, using the results of the research, many economic problems, such as unemployment, will be solved by managers by preparing tourism maps and creating service jobs for tourists. With the OWA method, tourism zoning maps can be controlled by managers in order to provide better services and social and economic justice.