Discriminating the occurrence of pitch canker fungus in Pinus radiata trees using QuickBird imagery and artificial neural networks

摘要: Pathogenic fungi, such as Fusarium circinatum, present a serious threat to Pinus radiata plantations. The effective management of infected trees is thus paramount. Coupled with advanced techniques, high spatial resolution remote sensing data provides the necessary tools effectively identify and map trees. This paper explores utility transformed QuickBird imagery artificial neural networks for detection mapping pitch canker disease. Individual tree crowns were delineated using an automated segmentation classification approach within object-based image analysis environment. Subsequently, several vegetation indices including tasseled cap transformation calculated incorporated into network model. feed-forward showed discriminatory power overall accuracy 82.15% KHAT 0.65. results this study show great potential future application crown-level can...