Land cover analysis of two university campuses: Examination over satellite images by Chat GPT

Abstract

Land Use and Land Cover Analysis are important in detecting the changes in urban areas, rural areas, and focused lands like university campuses. The availability of high-quality satellite images from diverse time sequences makes evaluations for changes by time possible. The analysis methods include insights from remote sensing fields to Artificial intelligence (AI) tools. AI has been significantly developed in the last decades in various fields, and applications of AI on satellite imagery analysis are being influenced. This study explores the capability of Chat GPT, which is one of the leading Language Models and can generate prompts and analysis due to inputs for Land Cover and Use Analysis. Firstly, an unstructured conversation with Chat GPT was held, and then, considering this experience, a land cover change analysis was executed for two university campuses. Besides, the analysis was also re-executed in Colab with codes generated by Chat GPT to seek differences. Two university campuses, Erzurumm Technical University and Adıyaman University, founded in the last two decades, were utilized as case studies. Chat GPT explained the steps and procedure of the analysis in detail generated codes in a defined framework. The analysis results have problems in classifying the land cover; however, the imperviousness change analysis shows most of the construction improvement. The experiment and findings have important implications for future research in Land Cover analysis implementing AI tools.

Keywords

• Chat GPT
• Colab
• Construction Track
• Land Cover
• University Campus

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