Urban development modeling using a fuzzy neuro-inference system with futures studies in Hajiabad City, Hormozgan Province

Document Type : Original Research Articles

Authors

Department of Geography, Faculty of Humanities, Islamic Azad University, Larestan Branch, Larestan, Iran.

Abstract

This study, with the aim of analyzing and predicting the physical changes of Hajiabad city, used the integration of the Neuro-Fuzzy Inference System (ANFIS) with the Autonomous Cell-Markov (CA-Markov) model. The results of the evaluation of the ANFIS model, with a correlation coefficient of 0.9678 and an overall accuracy of 23.91 in 2025, confirmed the high efficiency of this intelligent approach in analyzing the nonlinear relationships between environmental factors and urban development. The 20-year trend analysis (2005-2025) showed that residential land increased by 9.4% from 3304.5 to 3617.7 hectares, while barren land decreased by 435 hectares and medium pastures decreased by 230 hectares, experiencing the greatest land use change. The model’s predictions for the 2055 horizon indicate a significant jump in residential area to 4425.2 hectares, which means an increase of 22% compared to the current situation and the swallowing of about 653 units of barren land and 344 hectares of quality pastures in the region. The analysis of the drivers also revealed that “distance from roads” with a coefficient of 0.93 and “distance from built-up area” with a coefficient of 0.92 are the main drivers of the city’s physical expansion in the coming decades. Finally, the stability of 0.992 in the residential transition matrix indicates the definitive and irreversible consolidation of natural lands into urban spaces, which doubles the necessity of smart land management. The role of futures research in this paper is to transform dead satellite data into a living roadmap for the management of Hajiabad city for the next 30 years to prevent excessive development and ecological destruction.

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References

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Geography and Regional Future Studies
Volume 4, Issue 3 - Serial Number 15
Autumn
December 2026
Pages 121-143

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