TY - JOUR AB - The detection of pest infestation is an important aspect of forest management. In the case of the oak splendour beetle (Agrilus biguttatus) infestation, the affected oaks (Quercus sp.) show high levels of defoliation and altered canopy reflection signature. These critical features can be identified in high-resolution colour infrared (CIR) images of the tree crown and branches level captured by Unmanned Aerial Systems (UAS). In this study, we used a small UAS equipped with a compact digital camera which has been calibrated and modified to record not only the visual but also the near infrared reflection (NIR) of possibly infested oaks. The flight campaigns were realized in August 2013, covering two study sites which are located in a rural area in western Germany. Both locations represent small-scale, privately managed commercial forests in which oaks are economically valuable species. Our workflow includes the CIR/NIR image acquisition, mosaicking, georeferencing and pixel-based image enhancement followed by object-based image classification techniques. A modified Normalized Difference Vegetation Index (NDVImod) derived classification was used to distinguish between five vegetation health classes, i.e., infested, healthy or dead branches, other vegetation and canopy gaps. We achieved an overall Kappa Index of Agreement (KIA) of 0.81 and 0.77 for each study site, respectively. This approach offers a low-cost alternative to private forest owners who pursue a sustainable management strategy. AU - Lehmann, Jan Rudolf Karl AU - Nieberding, Felix AU - Nieberding, Felix Heinrich AU - Prinz, Torsten AU - Knoth, Christian DA - 2015-03-02 DO - doi:10.3390/f6030594 KW - autonomous flying KW - beetle infection KW - drone KW - GIS KW - NDVI KW - object-based image analysis KW - OBIA KW - UAV LA - eng N1 - Forests 6 (2015) 3, 594-612 N1 - Finanziert durch den Open-Access-Publikationsfonds 2014/2015 der Deutschen Forschungsgemeinschaft (DFG) und der Westfälischen Wilhelms-Universität Münster (WWU Münster). PY - 2015-03-02 SN - 1999-4907 TI - Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels UR - https://nbn-resolving.org/urn:nbn:de:hbz:6-00329474874 Y2 - 2024-12-04T09:02:37 ER -