UAV/SATELLITE MULTISCALE DATA FUSION FOR CROP MONITORING AND EARLY STRESS DETECTION

24 citations as recorded by crossref.

1. Past and Future of Plant Stress Detection: An Overview From Remote Sensing to Positron Emission Tomography A. Galieni et al. 10.3389/fpls.2020.609155
2. High spatio-temporal monitoring of century-old biochar effects on evapotranspiration through the ETLook model: a case study with UAV and satellite image fusion based on additive wavelet transform (AWT) R. Heidarian Dehkordi et al. 10.1080/15481603.2021.2016262
3. Urban tree species classification using UAV-based multi-sensor data fusion and machine learning S. Hartling et al. 10.1080/15481603.2021.1974275
4. Applications of UAV Thermal Imagery in Precision Agriculture: State of the Art and Future Research Outlook G. Messina & G. Modica 10.3390/rs12091491
5. Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity L. Kooistra et al. 10.5194/bg-21-473-2024
6. GIS approaches to creating maps based on vegetation indices for forest management Y. Savchenko et al. 10.1088/1757-899X/828/1/012021
7. UAV Data as an Alternative to Field Sampling to Monitor Vineyards Using Machine Learning Based on UAV/Sentinel-2 Data Fusion X. Zhou et al. 10.3390/rs13030457
8. Modeling of Diurnal Changing Patterns in Airborne Crop Remote Sensing Images D. Ma et al. 10.3390/rs13091719
9. High-resolution satellite imagery applications in crop phenotyping: An overview C. Zhang et al. 10.1016/j.compag.2020.105584
10. The Role of Remote Sensing in Olive Growing Farm Management: A Research Outlook from 2000 to the Present in the Framework of Precision Agriculture Applications G. Messina & G. Modica 10.3390/rs14235951
11. Faba bean above-ground biomass and bean yield estimation based on consumer-grade unmanned aerial vehicle RGB images and ensemble learning Y. Ji et al. 10.1007/s11119-023-09997-5
12. A grid-level segmentation model based on encoder-decoder structure with multi-source features for crop lodging detection L. Wang & H. Xiao 10.1016/j.asoc.2023.111113
13. Assessing the Potential of 10-m Resolution TVDI Based on Downscaled LST to Monitor Soil Moisture in Tang River Basin, China L. Cheng et al. 10.3390/rs15030744
14. Estimation of Agronomic Characters of Wheat Based on Variable Selection and  Machine Learning Algorithms D. Wang et al. 10.3390/agronomy13112808
15. Comparison of UAS and Sentinel-2 Multispectral Imagery for Water Quality Monitoring: A Case Study for Acid Mine Drainage Affected Areas (SW Spain) M. Isgró et al. 10.3390/rs14164053
16. Comparison of UAV and SAR performance for Crop type classification using machine learning algorithms: a case study of humid forest ecology experimental research site of West Africa O. Duke et al. 10.1080/01431161.2022.2109444
17. A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping T. Gill et al. 10.1007/s43657-022-00048-z
18. Estimating Crop Seed Composition Using Machine Learning from Multisensory UAV Data K. Dilmurat et al. 10.3390/rs14194786
19. Technology and Data Fusion Methods to Enhance Site-Specific Crop Monitoring U. Ahmad et al. 10.3390/agronomy12030555
20. High-Throughput Plant Phenotyping Platform (HT3P) as a Novel Tool for Estimating Agronomic Traits From the Lab to the Field D. Li et al. 10.3389/fbioe.2020.623705
21. Evaluation of a Baseline Controller for Autonomous “Figure-8” Flights of a Morphing Geometry Quadcopter: Flight Performance Y. Bai & S. Gururajan 10.3390/drones3030070
22. Soybean yield prediction from UAV using multimodal data fusion and deep learning M. Maimaitijiang et al. 10.1016/j.rse.2019.111599
23. Crop Monitoring Using Satellite/UAV Data Fusion and Machine Learning M. Maimaitijiang et al. 10.3390/rs12091357
24. A Comprehensive Survey of the Recent Studies with UAV for Precision Agriculture in Open Fields and Greenhouses M. Aslan et al. 10.3390/app12031047