UNLOCKING THE POTENTIAL OF HIGH-RESOLUTION REMOTE SENSING DATA: REVOLUTIONIZING PLANTATION MAPPING.

Advanced remote sensing technology is rapidly improving the ability to map plantations with specialized satellite sensors and advanced image analysis. This technology has the potential to transform the industry by allowing for precise vegetation mapping, health assessments, growth monitoring, and climate impact evaluations. Based on a review of relevant agricultural literature, the study emphasizes the importance of sub-meter pixel sizes in remote sensing applications for differentiating cover types and identifying landscape changes at the individual tree crown level. The integration of high-density data with geospatial processing and machine learning enables precise feature identification and classification, which is an important aspect of precision agriculture. This investigates the specific functions of various sensor types used in plantation monitoring, such as multispectral, thermal, LiDAR, and radar platforms, advocating for a approach that takes advantage of each's distinct strengths. This gives an overview of the most recent high-resolution optical satellites, demonstrating their ability to distinguish vegetation types, track changes over time, and extract useful attributes from images also discusses current monitoring techniques and their limitations before introducing advanced analytical methods for extracting valuable insights from dense data streams, such as classification, object-based image analysis, and deep learning. It discusses upcoming advancements such as improved spatial, spectral, and temporal resolution, increased 3D point cloud density through new LiDAR technologies, and AI-powered cloud computing tools for automated processing and analysis. Despite current challenges, the increasing availability of high-resolution remote sensing technology points to changes in the complexity of plantation mapping and improved management via data-rich insights. [ABSTRACT FROM AUTHOR]