Моніторинг та відновлення сільськогосподарських земель засобами штучного інтелекту

Abstract

This research examines the analysis and classification of agricultural land damage using aerial photography, and also methods for predicting the time required for their restoration. Utilizing modern machine learning technologies, an architecture for an intelligent decision support system has been proposed to identify soil damage and predict recovery timelines. The system comprises three AI models. The results aim to enhance decision-making processes in the restoration of agricultural resources, promoting sustainable management of lands post-conflict.