نوع مقاله : پژوهشی کاربردی
نویسندگان
1 عضو هیئت علمی، پژوهشکده حفاظت آب و خاک و آبخیزداری. تهران، ایران
2 کارشناس ارشد، گروه ریاضی، دانشگاه سیستان و بلوچستان، زاهدان، ایران
3 دکترا، گروه ژئومورفولوژی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
The use of Artificial Intelligence (AI) in managing natural and human hazards in mountainous areas has the potential to reduce damage and enhance resilience. This study, through a review of library-based studies and practical examples, analyzes the application of AI in managing earthquake hazards, slope movements, floods, forest fires, vegetation degradation, and urban development. The general information in this research is based on library studies, but in the practical examples section, satellite images from MODIS, Sentinel-1, and Landsat were used. The main tools used in this study were GMT, TerrSet, Google Earth Engine, and ArcGIS. In order to examine the effects of artificial intelligence on environmental hazard management in mountainous areas, the study investigates the importance of using this technology in addressing earthquake hazards, landslides, floods, vegetation degradation, fires, physical urban development, and water resource pollution. The results of this study have shown that for natural hazards, artificial intelligence, by integrating multi-source data, has been able to provide more accurate predictions compared to traditional methods. This higher accuracy not only increases response time but also enables preventive planning and reduces human and financial losses. For example, flood prediction with LSTM models and early warning of landslides using CNN are practical examples of these capabilities. In the field of human hazards, AI acts as an advanced analytical tool and early warning system. These include continuous monitoring of vegetation changes with the NDVI index, rapid detection of fires with convolutional neural networks, and modeling of pollutant pathways in aquifers, demonstrating the high capabilities of this technology in protecting sensitive mountain ecosystems. Based on the obtained results, this technology, with its capability to process vast amounts of data and identify complex patterns, can serve as an efficient and innovative tool for predicting, monitoring, and mitigating the impacts of these hazards.
کلیدواژه‌ها [English]
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