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The accurate detection and mapping of plant invasions is important for an effective weed management strategy in forest plantations. In this study, the utility of WorldView-2 was investigated to automatically map the occurrence of Solanum mauritianum (bugweed) found as an anomaly in forest margins, open areas and riparian zones. The unsupervised methodology developed, proved to be an effective and...
This study presents a novel unsupervised framework for mapping the invasive scrub, Solanum mauritianum (bugweed), as anomalies within riparian zones of a forest plantation using airborne AISA Eagle hyperspectral data (393 nm#x2013;994 nm). Utilizing an unsupervised random forest (RF) approach, the proximity matrix and Anselin local Moran's I anomaly detection reveal that the integration of LiDAR with...
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