## 5 Conclusions  
This study has demonstrated the efficacy of integrating AHP, GIS, and machine learning techniques to assess urban land suitability and forecast future urban growth in the Mersin Metropolitan Area. Through the generation of an urban land use suitability map and simulation of urban growth scenarios, valuable insights have been gleaned for sustainable urban development planning.  
Key findings reveal spatial patterns of land suitability, highlighting areas with varying degrees of suitability for urbanization. The analysis underscores the importance of considering diverse criteria such as topography, accessibility, soil capability, and geology in urban planning processes to ensure informed decision-making. Crucially, the study elucidates the potential impacts of future urban growth on the landscape, facilitating the identification of suitable areas for development while minimizing environmental degradation and preserving natural resources.  
GIS and remote sensing technologies play a vital role in urban growth and land use suitability research. These tools enable researchers to collect, analyze, and visualize spatial data, providing valuable information on land use patterns, environmental changes, and demographic trends. By integrating GIS and remote sensing techniques, researchers can conduct comprehensive spatial analyses and identify suitable areas for urban development. These technologies also facilitate the monitoring of urban growth over time and support the formulation of strategic plans for future development.  
Despite its contributions, this research has several limitations that should be acknowledged. One limitation is the challenge of data acquisition, particularly in obtaining accurate and comprehensive datasets for analysis. The resolution of available data sources may also affect the scale and scope of the research. Additionally, the exclusion of certain criteria, such as fault line datasets, may limit the comprehensiveness of the analysis. These limitations underscore the need for continued efforts to improve data quality and accessibility in future research endeavors.  
Future studies in urban growth and land use suitability research should address the limitations identified in this research and explore new avenues for analysis. Incorporating additional criteria, such as vertical growth considerations and climate change data, can enhance the comprehensiveness of future studies. Moreover, expanding the scope of analysis to include qualitative assessments and societal implications will provide a more holistic understanding of urbanization processes. Continued advancements in GIS and remote sensing technologies will also offer opportunities for conducting more detailed and accurate spatial analyses.  
Conceptualization, E.S. and M.C.I.; methodology, E.S., M.C.I. and S.S.B.; software, E.S., M.C.I. and S.S.B.; validation E.S., M.C.I. and S.S.B.; data curation, E.S.; writing--original draft preparation, E.S., M.C.I. and S.S.B.; writing--review and editing, E.S., M.C.I. and S.S.B.; visualization, E.S.; supervision, M.C.I. and S.S.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
This study is the master's dissertation research (Department of GIS and Remote Sensing at Mersin University) of the first author, supervised by the second and the third author. We would like to acknowledge the journal editor and anonymous reviewers for their constructive comments. We express our gratitude to [PERSON], [PERSON], and [PERSON] for their valuable insights and constructive comments provided during the analysis conducted in this research.  
The authors declare no conflicts of interest.