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

29 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. 10.3390/rs12030514
2. Use of UAV-Borne Spectrometer for Land Cover Classification S. Natesan et al. 10.3390/drones2020016
3. Monitoring the Severity of Rubber Tree Infected with Powdery Mildew Based on UAV Multispectral Remote Sensing T. Zeng et al. 10.3390/f14040717
4. Using Remote Sensing Vegetation Indices for the Discrimination and Monitoring of Agricultural Crops: A Critical Review R. Vidican et al. 10.3390/agronomy13123040
5. Detection of buried archaeological remains with the combined use of satellite multispectral data and UAV data J. Calleja et al. 10.1016/j.jag.2018.07.023
6. 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 10.3390/drones4010001
7. Estimation of maize yield and effects of variable-rate nitrogen application using UAV-based RGB imagery M. Zhang et al. 10.1016/j.biosystemseng.2019.11.001
8. Unmanned Aerial Vehicles (UAV) in Precision Agriculture: Applications and Challenges P. Velusamy et al. 10.3390/en15010217
9. UAV Platforms for Data Acquisition and Intervention Practices in Forestry: Towards More Intelligent Applications H. Sun et al. 10.3390/aerospace10030317
10. Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data A. Ashapure et al. 10.1016/j.isprsjprs.2020.09.015
11. Remote Sensing Satellites for Land Applications: A Review S. Kumar & V. Bhagat 10.21523/gcj1.18020203
12. UAS for Wetland Mapping and Hydrological Modeling J. Jeziorska 10.3390/rs11171997
13. A review of remote sensing for potato traits characterization in precision agriculture C. Sun et al. 10.3389/fpls.2022.871859
14. Wheat rust disease detection techniques: a technical perspective U. Shafi et al. 10.1007/s41348-022-00575-x
15. Recent Advances in Crop Disease Detection Using UAV and Deep Learning Techniques T. Shahi et al. 10.3390/rs15092450
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. 10.3390/s22197693
17. Application of remote monitoring and ground-based sensing in pastoralism S. Oleinik et al. 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. 10.1016/j.compag.2021.106033
19. UAV-Derived Multispectral Bathymetry L. Rossi et al. 10.3390/rs12233897
20. Experimental Evaluation and Consistency Comparison of UAV Multispectral Minisensors H. Lu et al. 10.3390/rs12162542
21. Assessing the Performance of UAS-Compatible Multispectral and Hyperspectral Sensors for Soil Organic Carbon Prediction G. Crucil et al. 10.3390/su11071889
22. Spectral Comparison of UAV-Based Hyper and Multispectral Cameras for Precision Viticulture S. Di Gennaro et al. 10.3390/rs14030449
23. Physical stream quality measured by drones and image analysis versus the traditional manual method N. Svane et al. 10.1080/09593330.2020.1824022
24. Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review K. Neupane & F. Baysal-Gurel 10.3390/rs13193841
25. Potato late blight severity monitoring based on the relief-mRmR algorithm with dual-drone cooperation H. Sun et al. 10.1016/j.compag.2023.108438
26. Automated Counting of Tobacco Plants Using Multispectral UAV Data H. Lin et al. 10.3390/agronomy13122861
27. Consumer-grade UAV imagery facilitates semantic segmentation of species-rich savanna tree layers M. Popp & J. Kalwij 10.1038/s41598-023-40989-7
28. Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics M. Ludwig et al. 10.3390/rs12223831
29. Improved Real-Time Semantic Segmentation Network Model for Crop Vision Navigation Line Detection M. Cao et al. 10.3389/fpls.2022.898131