USING MULTITEMPORAL HYPER- AND MULTISPECTRAL UAV IMAGING FOR DETECTING BARK BEETLE INFESTATION ON NORWAY SPRUCE

27 citations as recorded by crossref.

1. European beech spring phenological phase prediction with UAV-derived multispectral indices and machine learning regression S. Krause & T. Sanders 10.1038/s41598-024-66338-w
2. Multispectral Imagery Provides Benefits for Mapping Spruce Tree Decline Due to Bark Beetle Infestation When Acquired Late in the Season S. Junttila et al. 10.3390/rs14040909
3. UAV-Based Forest Health Monitoring: A Systematic Review S. Ecke et al. 10.3390/rs14133205
4. Bark beetle pre-emergence detection using multi-temporal hyperspectral drone images: Green shoulder indices can indicate subtle tree vitality decline L. Huo et al. 10.1016/j.isprsjprs.2024.07.027
5. What Is the Effect of Quantitative Inversion of Photosynthetic Pigment Content in Populus euphratica Oliv. Individual Tree Canopy Based on Multispectral UAV Images? Y. Kahaer et al. 10.3390/f13040542
6. Feasibility study of forest wood-boring pest detection base on hyperspectral LiDAR H. Shao et al. 10.1080/01431161.2024.2320180
7. Estimation of Tree Vitality Reduced by Pine Needle Disease Using Multispectral Drone Images L. Huo et al. 10.3390/rs17020271
8. Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data A. Fernandez-Carrillo et al. 10.3390/rs12213634
9. Spruce Bark Beetle Outbreak Prediction through Automatic Classification of Sentinel-2 Imagery A. Bozzini et al. 10.3390/f14061116
10. Remote sensing of bark beetle damage in Norway spruce individual tree canopies using thermal infrared and airborne laser scanning data fusion A. Zakrzewska & D. Kopeć 10.1016/j.fecs.2022.100068
11. RPAS-Based forest plantation health monitoring: an overview of recent progress S. da Silva et al. 10.1080/01431161.2024.2406036
12. Multispectral drone images for the early detection of bark beetle infestations: assessment over large forest areas in the Italian South-Eastern Alps A. Bozzini et al. 10.3389/ffgc.2025.1532954
13. Uncovering Early Traces of Bark Beetle Induced Forest Stress via Semantically Enriched Sentinel-2 Data and Spectral Indices L. Mandl & S. Lang 10.1007/s41064-023-00240-4
14. Early Detection of Bark Beetle Attack Using Remote Sensing and Machine Learning: A Review S. Marvasti-Zadeh et al. 10.1145/3625387
15. Hyperspectral reflectance measurements from UAS under intermittent clouds: Correcting irradiance measurements for sensor tilt C. Köppl et al. 10.1016/j.rse.2021.112719
16. Early Detection of Southern Pine Beetle Attack by UAV-Collected Multispectral Imagery C. Kanaskie et al. 10.3390/rs16142608
17. High Spatial and Temporal Resolution Energy Flux Mapping of Different Land Covers Using an Off-the-Shelf Unmanned Aerial System J. Simpson et al. 10.3390/rs13071286
18. Mapping European Spruce Bark Beetle Infestation at Its Early Phase Using Gyrocopter-Mounted Hyperspectral Data and Field Measurements F. Hellwig et al. 10.3390/rs13224659
19. Sensitivity analysis of the Green Shoulder indices in pre-emergence detection of single trees attacked by European spruce bark beetle L. Huo et al. 10.1080/01431161.2025.2482747
20. Early Detection of Dendroctonus valens Infestation at Tree Level with a Hyperspectral UAV Image B. Gao et al. 10.3390/rs15020407
21. Physically based illumination correction for sub-centimeter spatial resolution hyperspectral data O. Ihalainen et al. 10.1016/j.rse.2023.113810
22. Automatic Detection of Phytophthora pluvialis Outbreaks in Radiata Pine Plantations Using Multi-Scene, Multi-Temporal Satellite Imagery N. Camarretta et al. 10.3390/rs16020338
23. Early Detection of Dendroctonus valens Infestation with Machine Learning Algorithms Based on Hyperspectral Reflectance B. Gao et al. 10.3390/rs14061373
24. Drone-based early detection of bark beetle infested spruce trees differs in endemic and epidemic populations A. Bozzini et al. 10.3389/ffgc.2024.1385687
25. Exploring forest changes in an Ips typographus L. outbreak area: insights from multi-temporal multispectral UAS remote sensing M. Östersund et al. 10.1007/s10342-024-01734-5
26. Spectral signatures discrimination of Norway spruce trees under experimentally induced drought and acute thermal stress using hyperspectral imaging M. Pivovar et al. 10.1016/j.foreco.2025.122692
27. UAV-Based Hyperspectral Imagery for Detection of Root, Butt, and Stem Rot in Norway Spruce B. Allen et al. 10.3390/rs14153830