UAV MULTISPECTRAL SURVEY TO MAP SOIL AND CROP FOR PRECISION FARMING APPLICATIONS

11 citations as recorded by crossref.

1. Review of Photogrammetric and Lidar Applications of UAV Ľ. Kovanič et al. 10.3390/app13116732
2. Canopy Top, Height and Photosynthetic Pigment Estimation Using Parrot Sequoia Multispectral Imagery and the Unmanned Aerial Vehicle (UAV) V. Kopačková-Strnadová et al. 10.3390/rs13040705
3. Advanced Electronic and Optoelectronic Sensors, Applications, Modelling and Industry 5.0 Perspectives A. Massaro 10.3390/app13074582
4. Role of Unmanned Aerial Systems for Natural Resource Management P. Mishra & A. Rai 10.1007/s12524-020-01230-4
5. An Automated Machine Learning Framework in Unmanned Aircraft Systems: New Insights into Agricultural Management Practices Recognition Approaches K. Li et al. 10.3390/rs13163190
6. Disentangling Soil, Shade, and Tree Canopy Contributions to Mixed Satellite Vegetation Indices in a Sparse Dry Forest H. Wang et al. 10.3390/rs14153681
7. Multispectral and Thermal Sensors Onboard UAVs for Heterogeneity in Merlot Vineyard Detection: Contribution to Zoning Maps L. Atencia Payares et al. 10.3390/rs15164024
8. Implementation of Socket Priority Module for Unmanned Aerial Vehicle Network using FlyNetSimulator J. Windiatmaja et al. 10.1088/1757-899X/1077/1/012021
9. Implementing Cloud Computing for the Digital Mapping of Agricultural Soil Properties from High Resolution UAV Multispectral Imagery S. Pizarro et al. 10.3390/rs15123203
10. Estimation of soil moisture content under high maize canopy coverage from UAV multimodal data and machine learning M. Cheng et al. 10.1016/j.agwat.2022.107530
11. The Application of RGB, Multispectral, and Thermal Imagery to Document and Monitor Archaeological Sites in the Arctic: A Case Study from South Greenland J. Hollesen et al. 10.3390/drones7020115