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The tourism industry has become a major economic activity in the early years of the 21st Century and is considered one of the most productive and most employment-oriented global industries. Tourism is one of the most important factors generating wealth and employment in the world. It is necessary to plan for the proper exploitation of this industry, The most important steps to plan are to locate sites for providing tourists with the services they need in the form of tourist villages, This research is for the city of Shush which is one of the most important tourist areas of Khuzestan province And since it has many ancient monuments, it has attracted many tourists, , But the city has been at a very low level in terms of having a space worthy of tourists. Therefore, the conditions reinforced the idea of creating a tourism village. In this research, location-based discussion was conducted through a fuzzy inference system, Finally, the Fuzzy Topsis method has been used to protect the environment and to some extent extend sustainable tourism development. The ranking of these sites is based on environmental criteria. In the fuzzy inference system by applying the layers required in this method, four sites are considered to be very suitable.Then, using Fuzzy Topsis, which includes 10 criteria and 4 options, identified the best site on site 4. This site will bring the least damage to the environment, Located on the banks of the Dez River, most of the area has been covered by ground. In terms of maintaining environmental criteria, the site has a completely organic environment than other sites.

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Using urban growth and development modeling, it is possible to draw a development trend appropriate to the city's position according to environmental and natural factors and population attraction. The purpose of this study is to represent a model of urban development in Shushtar that can be used as a felicitous tool to analyze the complex processes of urban development. To achieve this goal, two databases consist of urban land use maps for educational, medical, habitation, etc and Landsat satellite images for major land uses such as rivers, barren areas, forests, etc were used by GIS and MATLAB software environment in three time periods 1991, 2004 and 2014. Existing urban land use maps were updated by using Landsat satellite imagery after digitization. Then the effective parameters in urban development were entered as inputs with the adaptive neuro-fuzzy inference algorithm (ANFIS). in order to evaluate the performance of the proposed method, training for 1991 and 2004 was performed. the result of urban development forecasting using the algorithm was compared with the current situation in 2014. The results are very close to reality and with an accuracy of 93.7%. The land use change map, which is the result of the change detection process, can be prepared based on multi-time remote sensing images and combined with urban user maps, and the relevant consequences examined. The use of intelligent algorithms in this research has allowed us to execute modeling with high accuracy. The results are satisfactory and this development was predicted for the coming years.