SPECTRAL IMAGING FROM UAVS UNDER VARYING ILLUMINATION CONDITIONS

41 citations as recorded by crossref.

1. Assessing radiometric calibration methods for multispectral UAV imagery and the influence of illumination, flight altitude and flight time on reflectance, vegetation index and inversion of winter wheat AGB and LAI H. Zhu et al. https://doi.org/10.1016/j.compag.2024.108821
2. Radiometric Correction of Multispectral UAS Images: Evaluating the Accuracy of the Parrot Sequoia Camera and Sunshine Sensor P. Olsson et al. https://doi.org/10.3390/rs13040577
3. Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level R. Näsi et al. https://doi.org/10.3390/rs71115467
4. Field phenotyping of water stress at tree scale by UAV-sensed imagery: new insights for thermal acquisition and calibration D. Gómez-Candón et al. https://doi.org/10.1007/s11119-016-9449-6
5. Illumination Correction of Multi-Time RGB Images Obtained with an Unmanned Aerial Vehicle M. Kataev et al. https://doi.org/10.33383/2020-038
6. Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows H. Aasen et al. https://doi.org/10.3390/rs10071091
7. Radiometric Correction of Close-Range Spectral Image Blocks Captured Using an Unmanned Aerial Vehicle with a Radiometric Block Adjustment E. Honkavaara & E. Khoramshahi https://doi.org/10.3390/rs10020256
8. Biases in estimated vegetation indices from observations under cloudy conditions K. Wolf et al. https://doi.org/10.5194/bg-22-7797-2025
9. Water resource management at catchment scales using lightweight UAVs: current capabilities and future perspectives L. DeBell et al. https://doi.org/10.1139/juvs-2015-0026
10. Drones in agriculture: A review and bibliometric analysis A. Rejeb et al. https://doi.org/10.1016/j.compag.2022.107017
11. Field Calibration of Hyperspectral Cameras for Terrain Inference N. Hanson et al. https://doi.org/10.1109/LRA.2025.3617735
12. Data-Driven Artificial Intelligence for Calibration of Hyperspectral Big Data V. Sagan et al. https://doi.org/10.1109/TGRS.2021.3091409
13. Evaluation of Incident Light Sensors on Unmanned Aircraft for Calculation of Spectral Reflectance E. Hunt & A. Stern https://doi.org/10.3390/rs11222622
14. Direct Reflectance Measurements from Drones: Sensor Absolute Radiometric Calibration and System Tests for Forest Reflectance Characterization T. Hakala et al. https://doi.org/10.3390/s18051417
15. Impact of the reproductive organs on crop BRDF as observed from a UAV W. Li et al. https://doi.org/10.1016/j.rse.2021.112433
16. Mapping Mosaic Virus in Sugarcane Based on Hyperspectral Images E. Moriya et al. https://doi.org/10.1109/JSTARS.2016.2635482
17. Assessing the impact of illumination on UAV pushbroom hyperspectral imagery collected under various cloud cover conditions J. Arroyo-Mora et al. https://doi.org/10.1016/j.rse.2021.112396
18. Processing and Assessment of Spectrometric, Stereoscopic Imagery Collected Using a Lightweight UAV Spectral Camera for Precision Agriculture E. Honkavaara et al. https://doi.org/10.3390/rs5105006
19. Quality Assessment of the Bidirectional Reflectance Distribution Function for NIR Imagery Sequences from UAV D. Wierzbicki et al. https://doi.org/10.3390/rs10091348
20. Mini-UAV-Borne Hyperspectral Remote Sensing: From Observation and Processing to Applications Y. Zhong et al. https://doi.org/10.1109/MGRS.2018.2867592
21. Remote Sensing of 3-D Geometry and Surface Moisture of a Peat Production Area Using Hyperspectral Frame Cameras in Visible to Short-Wave Infrared Spectral Ranges Onboard a Small Unmanned Airborne Vehicle (UAV) E. Honkavaara et al. https://doi.org/10.1109/TGRS.2016.2565471
22. Imaging from manned ultra-light and unmanned aerial vehicles for estimating properties of spring wheat G. Mozgeris et al. https://doi.org/10.1007/s11119-018-9562-9
23. On-Site Devices for Precision Agriculture Applications: A Review of Soil and Plant Sensors N. Ljubičić et al. https://doi.org/10.3390/agriculture16080883
24. Estimation of vegetation fraction using RGB and multispectral images from UAV M. Marcial-Pablo et al. https://doi.org/10.1080/01431161.2018.1528017
25. Calibration and Validation from Ground to Airborne and Satellite Level: Joint Application of Time-Synchronous Field Spectroscopy, Drone, Aircraft and Sentinel-2 Imaging P. Naethe et al. https://doi.org/10.1007/s41064-022-00231-x
26. Relative Radiometric Calibration Using Tie Points and Optimal Path Selection for UAV Images J. Shin et al. https://doi.org/10.3390/rs12111726
27. Mapping Crop Leaf Area Index and Canopy Chlorophyll Content Using UAV Multispectral Imagery: Impacts of Illuminations and Distribution of Input Variables W. Li et al. https://doi.org/10.3390/rs15061539
28. Influence of the Sun Position and Platform Orientation on the Quality of Imagery Obtained from Unmanned Aerial Vehicles A. Sekrecka et al. https://doi.org/10.3390/rs12061040
29. Design of Vegetation Index for Identifying the Mosaic Virus in Sugarcane Plantation: A Brazilian Case Study É. Moriya et al. https://doi.org/10.3390/agronomy13061542
30. Accurate Conversion of Land Surface Reflectance for Drone-Based Multispectral Remote Sensing Images Using a Solar Radiation Component Separation Approach H. Sun et al. https://doi.org/10.3390/s25082604
31. Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance H. Aasen et al. https://doi.org/10.1016/j.isprsjprs.2015.08.002
32. Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging O. Nevalainen et al. https://doi.org/10.3390/rs9030185
33. Bidirectional Reflectance Distribution Function Modeling Considerations in Small Unmanned Multispectral Systems R. Fischer et al. https://doi.org/10.1109/JSTARS.2022.3171393
34. Assessing Pacific Madrone Blight with UAS Remote Sensing Under Different Skylight Conditions M. Winfield et al. https://doi.org/10.3390/rs17183141
35. Assessing the status of forest regeneration using digital aerial photogrammetry and unmanned aerial systems T. Goodbody et al. https://doi.org/10.1080/01431161.2017.1402387
36. Drones in urban stormwater management: a review and future perspectives W. McDonald https://doi.org/10.1080/1573062X.2019.1687745
37. Radiometric block adjustment of hyperspectral image blocks in the Brazilian environment G. Miyoshi et al. https://doi.org/10.1080/01431161.2018.1425570
38. Radiometric and Atmospheric Corrections of Multispectral μMCA Camera for UAV Spectroscopy R. Minařík et al. https://doi.org/10.3390/rs11202428
39. An Empirical Assessment of Angular Dependency for RedEdge-M in Sloped Terrain Viticulture C. Gong et al. https://doi.org/10.3390/rs11212561
40. UAV-hyperspectral imaging of spectrally complex environments B. Banerjee et al. https://doi.org/10.1080/01431161.2020.1714771
41. Monitoring spring phenology of individual tree crowns using drone‐acquired NDVI data D. Fawcett et al. https://doi.org/10.1002/rse2.184