3.Assessment of Climatic and Geomorphological Factors in Military Base Site Selection Using Remote Sensing and GIS: (Case Study of the Moghan Plain, Ardabil Province)

Document Type : Extract article from research project

Authors

1 Professor, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran

2 Ph.D Student, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.

Abstract
Background and Objective: Location selection is one of the strategic elements in the development of a country's defense infrastructure, requiring precise analysis of environmental, climatic, and human factors using modern spatial approaches. Therefore, the objective of this research is to investigate the role of climatic and geomorphological factors affecting the site selection of military garrisons in Moghan Plain, located in Ardabil Province, by utilizing remote sensing and GIS capabilities.
Methodology: To fulfill the research objective, 14 relevant criteria were selected, including precipitation, temperature, actual evapotranspiration, elevation, slope, aspect, vegetation cover, land use, distance from rivers, faults, roads, cities, villages, and geology. The required spatial layers were derived from remote sensing data sources such as Sentinel-2 imagery, the 12.5-meter ALOS PALSAR Digital Elevation Model, and global climate datasets including TerraClimate, and were processed within the Google Earth Engine (GEE) environment. Subsequently, training sample points representing suitable and unsuitable locations were defined, and the Random Forest (RF) algorithm was trained and applied to produce the final suitability zoning map.
Results and Findings: The variable importance analysis indicated that proximity to cities and villages, slope, vegetation cover, and distance from geological faults were the most influential factors in military base site selection within the study area. The final suitability map classified the region into five categories: very suitable, suitable, moderately suitable, unsuitable, and very unsuitable. Notably, portions of the northern and eastern sections of the Moghan Plain were identified as very suitable zones. This study demonstrates that the integration of machine learning algorithms with remote sensing data offers a robust and efficient approach for spatial analysis and supports strategic decision-making in the defense and military planning sectors.
Conclusion: The findings of this study can support the optimization of military base site selection by integrating strategic, environmental, and security-related criteria. Such an approach has the potential to enhance military operational efficiency, strengthen crisis management capabilities, reduce infrastructure development costs, and minimize vulnerability to natural hazards.

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  • Receive Date 04 January 2025
  • Revise Date 16 February 2025
  • Accept Date 17 April 2025
  • First Publish Date 17 April 2025
  • Publish Date 22 May 2026