Forests play a vital role in global ecosystems that provide essential environmental services such as carbon sequestration, biodiversity conservation, and watershed protection. Monitoring and understanding changes in forest land use and land cover (LULC) is crucial for effective management and conservation. This comprehensive chapter examines the latest technologies and methods employed in the analysis of forest LULC, highlighting their strengths, limitations, and potential applications. Remote sensing technologies have revolutionized forest monitoring by providing accurate and detailed information on forest dynamics. Satellite sensors, including multispectral and hyperspectral imagers and Light Detection and Ranging (LiDAR), offer valuable data on vegetation indices, forest structure, biomass estimation, and disturbance detection. Geographic Information Systems (GIS) allows the integration of diverse datasets, such as topographic information, climate data, and socio-economic variables, facilitating a comprehensive understanding of forest dynamics. Unmanned vehicles or UAVs have transformed the field of remote sensing and aerial imaging. With their ability to capture high-resolution imagery from various altitudes and perspectives, UAVs have revolutionized applications in agriculture, environmental monitoring, infrastructure inspection, disaster response, urban planning, and many other fields. Machine learning and artificial intelligence (AI) have emerged as powerful tools for forest LULC analysis. Advanced algorithms, such as random forests, support vector machines, and deep learning models, enhance the accuracy of classification and change detection tasks. AI-based approaches also enable the automatic extraction of forest attributes, such as tree species identification, forest age estimation, and deforestation hotspot identification. These methods contribute to more efficient and reliable monitoring processes. This review underscores the importance of leveraging a combination of remote sensing, GIS, and machine learning for robust forest LULC analysis. By harnessing these technologies and methods, researchers, policymakers, and forest managers can obtain accurate, timely, and actionable information to support sustainable forest management and conservation efforts in the face of increasing environmental challenges.