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This chapter explored how remote sensing and drone technologies transformed forest monitoring and management practices between 2015 to 2025. The objective was to assess their role in evaluating forest health, biodiversity, and carbon storage. A key research gap addressed was the limited understanding of how integrated platforms, combining satellites, drones, LiDAR, and vegetation indices, could offer more precise and scalable forest data. Using a conceptual framework and the Systematic Literature Review (SLR) technique for literature review, the study analyzed tools such as Landsat, Sentinel, MODIS, NDVI, EVI, and LiDAR to examine their applications in tracking deforestation, estimating biomass, and detecting illegal logging. The findings showed that merging satellite imagery with drone and ground-based sensors significantly improved the accuracy and frequency of forest assessments. Integration with GIS and machine learning further enhanced decision-making capabilities. Multi-source remote sensing enhances forest conservation, climate monitoring, policy development.