LIGHT-WEIGHT MULTISPECTRAL UAV SENSORS AND THEIR CAPABILITIES FOR PREDICTING GRAIN YIELD AND DETECTING PLANT DISEASES

32 citations as recorded by crossref.

1. Multi-Scale Evaluation of Drone-Based Multispectral Surface Reflectance and Vegetation Indices in Operational Conditions D. Fawcett et al. https://doi.org/10.3390/rs12030514
2. Use of UAV-Borne Spectrometer for Land Cover Classification S. Natesan et al. https://doi.org/10.3390/drones2020016
3. Monitoring the Severity of Rubber Tree Infected with Powdery Mildew Based on UAV Multispectral Remote Sensing T. Zeng et al. https://doi.org/10.3390/f14040717
4. Using Remote Sensing Vegetation Indices for the Discrimination and Monitoring of Agricultural Crops: A Critical Review R. Vidican et al. https://doi.org/10.3390/agronomy13123040
5. Prediction of Optical and Non-Optical Water Quality Parameters in Oligotrophic and Eutrophic Aquatic Systems Using a Small Unmanned Aerial System J. Arango & R. Nairn https://doi.org/10.3390/drones4010001
6. UAV Platforms for Data Acquisition and Intervention Practices in Forestry: Towards More Intelligent Applications H. Sun et al. https://doi.org/10.3390/aerospace10030317
7. Remote Sensing Satellites for Land Applications: A Review S. Kumar & V. Bhagat https://doi.org/10.21523/gcj1.18020203
8. UAS for Wetland Mapping and Hydrological Modeling J. Jeziorska https://doi.org/10.3390/rs11171997
9. Advancements in Automated Plant Disease Detection: a Comprehensive Review of Imaging Technologies and Deep Learning Applications R. Raju & T. Thasleema https://doi.org/10.1007/s10343-025-01247-0
10. Comparative assessment of bathymetric methods using unmanned aerial vehicle (UAV) high-resolution multispectral imaging S. Viaña-Borja et al. https://doi.org/10.1016/j.coastaleng.2025.104854
11. A review of remote sensing for potato traits characterization in precision agriculture C. Sun et al. https://doi.org/10.3389/fpls.2022.871859
12. Optimizing Data Consistency in UAV Multispectral Imaging for Radiometric Correction and Sensor Conversion Models W. Yang et al. https://doi.org/10.3390/rs17122001
13. Wheat rust disease detection techniques: a technical perspective U. Shafi et al. https://doi.org/10.1007/s41348-022-00575-x
14. Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques T. Shahi et al. https://doi.org/10.3390/rs15092450
15. Advancements in UAV remote sensing for agricultural yield estimation: A systematic comprehensive review of platforms, sensors, and data analytics S. Gade et al. https://doi.org/10.1016/j.rsase.2024.101418
16. Evaluating the Performance of Airborne and Ground Sensors for Applications in Precision Agriculture: Enhancing the Postprocessing State-of-the-Art Algorithm K. Pavelka et al. https://doi.org/10.3390/s22197693
17. Application of remote monitoring and ground-based sensing in pastoralism S. Oleinik et al. https://doi.org/10.1051/bioconf/20236609007
18. A comprehensive review on recent applications of unmanned aerial vehicle remote sensing with various sensors for high-throughput plant phenotyping L. Feng et al. https://doi.org/10.1016/j.compag.2021.106033
19. UAV-Derived Multispectral Bathymetry L. Rossi et al. https://doi.org/10.3390/rs12233897
20. Experimental Evaluation and Consistency Comparison of UAV Multispectral Minisensors H. Lu et al. https://doi.org/10.3390/rs12162542
21. Assessing the Performance of UAS-Compatible Multispectral and Hyperspectral Sensors for Soil Organic Carbon Prediction G. Crucil et al. https://doi.org/10.3390/su11071889
22. Spectral Comparison of UAV-Based Hyper and Multispectral Cameras for Precision Viticulture S. Di Gennaro et al. https://doi.org/10.3390/rs14030449
23. Physical stream quality measured by drones and image analysis versus the traditional manual method N. Svane et al. https://doi.org/10.1080/09593330.2020.1824022
24. Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review K. Neupane & F. Baysal-Gurel https://doi.org/10.3390/rs13193841
25. Potato late blight severity monitoring based on the relief-mRmR algorithm with dual-drone cooperation H. Sun et al. https://doi.org/10.1016/j.compag.2023.108438
26. Automated Counting of Tobacco Plants Using Multispectral UAV Data H. Lin et al. https://doi.org/10.3390/agronomy13122861
27. Improving Radiometric Block Adjustment for UAV Multispectral Imagery under Variable Illumination Conditions Y. Wang et al. https://doi.org/10.3390/rs16163019
28. Consumer-grade UAV imagery facilitates semantic segmentation of species-rich savanna tree layers M. Popp & J. Kalwij https://doi.org/10.1038/s41598-023-40989-7
29. In-field proximal sensing of septoria tritici blotch, stripe rust and brown rust in winter wheat by means of reflectance and textural features from multispectral imagery R. Bebronne et al. https://doi.org/10.1016/j.biosystemseng.2020.06.011
30. Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics M. Ludwig et al. https://doi.org/10.3390/rs12223831
31. Improved Real-Time Semantic Segmentation Network Model for Crop Vision Navigation Line Detection M. Cao et al. https://doi.org/10.3389/fpls.2022.898131
32. Spectral Discrimination of Common Karoo Shrub and Grass Species Using Spectroscopic Data C. Harmse & A. van Niekerk https://doi.org/10.3390/rs16203869