Application of Random Forest Classification to Detect the Pine Wilt Disease from High Resolution Spectral Images
Autor: | N. Lewyckyj, Vasco Mantas, Elsa Baltazar, Niels Souverijns, Marian-Daniel Iordache |
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Rok vydání: | 2020 |
Předmět: |
010504 meteorology & atmospheric sciences
Computer science 0211 other engineering and technologies food and beverages Hyperspectral imaging High resolution 02 engineering and technology Vegetation 15. Life on land medicine.disease_cause 01 natural sciences Random forest Statistical classification Infestation medicine 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing Wilt disease |
Zdroj: | IGARSS |
Popis: | Pine Wilt Disease is one of the forest pests with high destructive potential, due to its random spreading and the fast evolution of the symptoms. The correct identification of infected trees is critical for the containment of the pest in affected areas. This paper exploits the capabilities of Random Forest classification algorithms designed to spot the infected trees based on remote sensing images. We use as input both multi- and hyperspectral imagery with high spatial resolution, acquired via remotely piloted airborne systems in infected Portuguese forests. For both imagery types, the classification schemes achieve accuracies higher than 0.91. We conclude that Random Forest classification is a feasible method to detect the Pine Wilt Disease in spectral images acquired over wild forests, even at early stages of the infestation. |
Databáze: | OpenAIRE |
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