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High spectral resolution multitemporal data were used to model asymptomatic stress caused by Fusarium circinatum in 3-month old Pinus radiata seedlings. The objectives of the study were: 1) to identify an optimal subset of wavebands that could model asymptomatic stress in P. radiata seedlings and 2) to develop a robust classification model for discriminating healthy and stressed seedlings. To achieve...
The random forest algorithm has been widely used for classification of hyperspectral data. To improve model interpretation and classification, the random forest algorithm is often combined with feature selection algorithms. It is within this context that we explore the utility of three random forest wrappers to compute an optimal subset of wavebands to discriminate healthy and stressed Pinus radiata...
Pitch canker is causing serious damage to Pinus radiata forests in South Africa. There is an urgent need to find an efficient way to assess the extent and variability of the disease at a broad spatial scale. The aim of this study is to explore the utility of transformed high spatial resolution QuickBird imagery and artificial neural networks, for the detection and mapping of pitch canker disease....
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