STUDYING REMOTE SENSING TECHNIQUES FOR FOREST RESOURCE MONITORING AND MANAGEMENT

REMOTE SENSING TECHNIQUES FOR FOREST RESOURCE MONITORING AND MANAGEMENT

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REMOTE SENSING TECHNIQUES FOR FOREST RESOURCE MONITORING AND MANAGEMENT

Abstract

This study examines the application of remote sensing techniques for forest resource monitoring and management, emphasizing their role in sustainable environmental planning. Remote sensing, through satellite imagery, aerial photography, and drone technologies, provides accurate, real-time data on forest cover, biomass estimation, deforestation, and ecosystem health. The research highlights how integrating Geographic Information Systems (GIS) with remote sensing enhances spatial analysis and decision-making in forest conservation. Using a combination of Landsat and Sentinel satellite data, the study assesses changes in forest density, species composition, and land-use patterns over a defined period. Findings reveal that remote sensing offers a cost-effective and reliable approach for detecting illegal logging, forest degradation, and fire outbreaks. The study concludes that the adoption of advanced techniques such as LiDAR, hyperspectral imaging, and machine learning-based image classification significantly improves forest resource assessment and supports evidence-based policy formulation. Recommendations include increased investment in remote sensing infrastructure, capacity building for forest managers, and the integration of multi-temporal datasets to strengthen sustainable forest management practices in Nigeria and beyond.

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