Document Type : Original Article
Extended Abstract
1. Introduction
Land use and land cover (LULC) change is a critical indicator of human impact on the environment, stemming from a complex interplay of human and natural drivers. Miandoab County in West Azerbaijan Province, Iran, serves as a prime example of a region under severe pressure from population growth, urbanization, and climate change. The unique geographical setting between two major rivers, Zarrineh-Rud and Simineh-Rud, makes it a pivotal agricultural hub, yet its long-term sustainability is challenged by these pressures. This necessitates a forward-looking analysis to scientifically predict future LULC trends.
This research aims to conduct a spatio-temporal analysis of LULC changes in Miandoab County from 2013 to 2024 and to predict these changes up to 2054 using the Cellular Automata-Markov (CA-Markov) model. This model is a powerful tool for simulating future scenarios due to its ability to integrate both temporal and spatial analyses. The Markov component calculates the transition probability matrix between two time periods, while the Cellular Automata component spatially distributes these probabilities based on neighborhood rules to simulate the future LULC map. Although the model has limitations, such as not directly incorporating socio-economic factors, its effectiveness in simulating spatio-temporal trends is well-established.
A review of the literature reveals a common pattern of urban and agricultural expansion at the expense of natural and fertile lands. Studies from Iran (e.g., Mashhad, Shiraz, Quchan) and other countries (e.g., Pakistan, China) confirm this trend. This study distinguishes itself by investigating a specific
Intra agricultural dynamicthe replacement of gardens with seasonal farms in response to water stress, a critical issue for Miandoab’s semi-arid climate.
2. Materials and Methods
2.1. Study Area: Miandoab County is located in a fertile plain between the Zarrineh-Rud and Simineh-Rud rivers. To provide a more focused analysis, the study area was a purposeful selection of the urban core and its connecting corridor, allowing for a more detailed modeling of urban development dynamics. The region has a semi-arid climate and an elevation of approximately 1300 meters above sea level. The landscape is a mix of seasonal farms, permanent gardens, and bare soils (saline and barren lands).
2.2. Research Methodology: This applied research used a mixed-methods (quantitative and qualitative) approach. The primary data were two atmospherically corrected (L2) Landsat 8 OLI satellite images from July 10, 2013, and July 8, 2024. The Maximum Likelihood Classification (MLC) algorithm was used to classify the images into five main LULC classes: Buildings, Soils, Farms, Gardens, and Water. The CA-Markov model was then employed to simulate the 2054 LULC map based on the transition matrix derived from the 2013-2024 data. The accuracy was validated using the Kappa coefficient, Overall Accuracy, Chi-square test, and Cramer's V index.
3. Results and Discussion
3.1. Analysis of 2013-2024 Changes: The classification showed that in 2013, Gardens (1781.28 ha) were the dominant LULC class. By 2024, this pattern had shifted dramatically. Farms (1977.21 ha) and Buildings (2041.56 ha) had expanded significantly, while Gardens (1466.37 ha) and especially Soils (638.82 ha) experienced a sharp decline. This trend indicates a shift toward seasonal farming and horizontal urban expansion, consuming fertile agricultural and bare lands.
3.2. Prediction for 2054: The CA-Markov model predicts an intensification of these trends. By 2054:
· Farms are projected to increase by approximately 1097 ha, reaching 3074.76 ha, becoming the most dominant class.
· Buildings are expected to grow by around 550 ha to 2592.09 ha.
· Gardens will face a catastrophic decline of over 1063 ha, shrinking to just 402.75 ha.
· Soils are predicted to be almost entirely consumed, decreasing by 555 ha to a mere 82.98 ha.
· Water resources are also expected to decrease to a critical level of 23.67 ha.
These findings align with international studies, such as research in China that predicted a significant loss of farmland. The specific trend of gardens being replaced by farms highlights the region's vulnerability to water stress, a phenomenon that should serve as a serious warning for semi-arid areas. The predicted landscape for 2054 is a simplified mosaic of farms and buildings, with severely depleted natural resources, signaling a future of chronic water and environmental stress.
4. Conclusions
The LULC changes in Miandoab reflect a critical imbalance between human development pressures and the region's ecological capacity. This trajectory poses severe threats to sustainability, including biodiversity loss, soil erosion, and heightened water stress. The 2054 prediction underscores the urgent need for a policy reassessment.
For sustainable land management, it is recommended to: 1) Prevent the conversion of gardens by implementing supportive policies and providing subsidies for modern irrigation systems. 2) Guide urban development toward barren lands and away from fertile agricultural soils. 3) Integrate socio-economic variables (e.g., land prices and population patterns) into future modeling to enhance realism and provide more effective policy tools.
5. Acknowledgment & Funding
This article is derived from the Master's thesis of Amirhosein Pasandeh, a student in Remote Sensing and Geographic Information Systems. We extend our gratitude to Mohaghegh Ardabili University for its material and spiritual support. The manuscript did not receive a grant from any organization.
6. Conflict of Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
