In the heart of Lorestan Province, Iran, a groundbreaking study is reshaping how we think about agricultural tourism and its potential to revitalize rural economies. Led by Mohammad Reza Rezvani, this research, published in Geographia va Paydari-e-Mahit (Geography and Environmental Sustainability), delves into the spatial zoning of agricultural tourism capabilities, offering a roadmap for sustainable rural development.
The agricultural sector has long been a cornerstone of rural economies, but declining productivity and income have forced many farmers to seek alternative livelihoods. Agricultural tourism has emerged as a promising strategy to diversify rural economies and promote sustainable development. However, the success of this strategy hinges on identifying areas with the right infrastructure and spatial conditions.
Rezvani’s study addresses this challenge by conducting a spatial analysis of agricultural tourism capabilities in Lorestan Province. Using a combination of Fuzzy-Analytic Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the research identifies key criteria for agricultural tourism development and ranks villages based on their potential.
“The most effective criteria for agricultural tourism development are the distance from agricultural plots and the distance from garden lands,” Rezvani explains. “These factors are crucial for attracting tourists and ensuring the sustainability of tourism activities.”
The study reveals that only 35% of the total area in Lorestan Province has high potential for agricultural tourism development. The most promising areas stretch from the southeast to the northeast, where the climate and agricultural lands are more favorable. In contrast, the northwest and southwest regions are deemed unsuitable due to their rugged terrain and inaccessibility.
Nasrabad village emerges as the most capable for agricultural tourism development, followed by Karimaabad and Kamandan villages. These findings provide valuable insights for investors, planners, and decision-makers, helping them identify optimal locations for tourism development.
The implications of this research are far-reaching. By providing a practical approach for spatial analysis of tourism potential, it enables the development of agricultural tourism in Lorestan Province and beyond. The model’s ability to consider uncertainty in the weight of criteria makes it a powerful tool for decision-making in the energy sector, where risk assessment is crucial.
As we look to the future, this research paves the way for more sophisticated spatial analysis models. Future studies could combine the capabilities of fuzzy hierarchical analysis with ordered weight combination models to incorporate risk parameters into decision-making processes. This could revolutionize how we approach agricultural tourism and rural development, ensuring that investments are made in the right places and that rural communities thrive.
