Forest cover loss alerts analysis is a module built using the SEPAL UI framework and Voila, a Python-based tool for creating interactive web applications. It provides a comprehensive solution for monitoring and analyzing forest cover loss alerts across various geographic regions and timeframes. By integrating data from multiple sources such as GLAD-L and GLAD-S2 (Global Land Analysis & Discovery), RADD (RAdar for Detecting Deforestation), and CCDC (Continuous Change Detection and Classification), the platform allows users to access, visualize, and analyze forest cover loss hotspots. Additionally, it leverages a deep learning Convolutional Neural Network (CNN) model to refine and improve the accuracy of forest cover loss alerts. The platform also includes user-friendly reporting features that assist users in creating detailed reports and offering valuable information to address forest cover loss issues.