LEAF AREA INDEX ESTIMATION IN VINEYARDS FROM UAV HYPERSPECTRAL DATA, 2D IMAGE MOSAICS AND 3D CANOPY SURFACE MODELS

41 citations as recorded by crossref.

1. In-Season Interactions between Vine Vigor, Water Status and Wine Quality in Terrain-Based Management-Zones in a ‘Cabernet Sauvignon’ Vineyard I. Bahat et al. 10.3390/rs13091636
2. Detection and Segmentation of Vine Canopy in Ultra-High Spatial Resolution RGB Imagery Obtained from Unmanned Aerial Vehicle (UAV): A Case Study in a Commercial Vineyard C. Poblete-Echeverría et al. 10.3390/rs9030268
3. Quantitative estimation of organ-scale phenotypic parameters of field crops through 3D modeling using extremely low altitude UAV images B. Zhu et al. 10.1016/j.compag.2023.107910
4. Unmanned aerial vehicles for biodiversity-friendly agricultural landscapes - A systematic review F. Librán-Embid et al. 10.1016/j.scitotenv.2020.139204
5. Thermoregulation capability of the leaf canopy according to canopy area and grapevine cultivar S. Vélez et al. 10.17660/ActaHortic.2024.1390.11
6. Individual Grapevine Analysis in a Multi-Temporal Context Using UAV-Based Multi-Sensor Imagery L. Pádua et al. 10.3390/rs12010139
7. Estimation of leaf area index in sagebrush steppe with low cost unoccupied aerial systems C. Woodruff et al. 10.1007/s10980-024-02031-7
8. Comparison of Crop Trait Retrieval Strategies Using UAV-Based VNIR Hyperspectral Imaging A. Abdelbaki et al. 10.3390/rs13091748
9. Evaluation of Crop Health Status With UAS Multispectral Imagery O. Vlachopoulos et al. 10.1109/JSTARS.2021.3132228
10. Comparison of Unsupervised Algorithms for Vineyard Canopy Segmentation from UAV Multispectral Images P. Cinat et al. 10.3390/rs11091023
11. Vineyard properties extraction combining UAS-based RGB imagery with elevation data L. Pádua et al. 10.1080/01431161.2018.1471548
12. Evaluating biostimulants via high-throughput field phenotyping: Biophysical traits retrieval through PROSAIL inversion G. Antonucci et al. 10.1016/j.atech.2022.100067
13. Global Leaf Area Index Research over the Past 75 Years: A Comprehensive Review and Bibliometric Analysis J. Ma et al. 10.3390/su15043072
14. High resolution aerial photogrammetry based 3D mapping of fruit crop canopies for precision inputs management R. Sinha et al. 10.1016/j.inpa.2021.01.006
15. Research on Leaf Area Index Inversion Based on LESS 3D Radiative Transfer Model and Machine Learning Algorithms Y. Jiang et al. 10.3390/rs16193627
16. Vineyard Variability Analysis through UAV-Based Vigour Maps to Assess Climate Change Impacts L. Pádua et al. 10.3390/agronomy9100581
17. A Review of Imaging and Sensing Technologies for Field Phenotyping L. Botyanszka 10.2478/ahr-2021-0011
18. Crop growth, carbon sequestration and soil erosion in an organic vineyard of the Villány Wine District, Southwest Hungary J. Dezső et al. 10.15201/hungeobull.69.3.4
19. Leaf area index estimations by deep learning models using RGB images and data fusion in maize P. Castro-Valdecantos et al. 10.1007/s11119-022-09940-0
20. Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery L. Pádua et al. 10.3390/rs10121907
21. Use of UAV-Borne Spectrometer for Land Cover Classification S. Natesan et al. 10.3390/drones2020016
22. Applications of Remote Sensing in Precision Agriculture: A Review R. Sishodia et al. 10.3390/rs12193136
23. Delineation of site-specific management zones for pest control purposes: Exploring precision agriculture and species distribution modeling approaches L. Méndez-Vázquez et al. 10.1016/j.compag.2019.105101
24. Missing Plant Detection in Vineyards Using UAV Angled RGB Imagery Acquired in Dormant Period S. Di Gennaro et al. 10.3390/drones7060349
25. The Delineation of Management Zones of the Halyomorpha halys (Hemiptera: Pentatomidae) Population Based on Its Spatiotemporal Distribution for Precision Agriculture Purposes V. Liakos et al. 10.3390/insects16040336
26. Mapping the Leaf Area Index of Castanea sativa Miller Using UAV-Based Multispectral and Geometrical Data L. Pádua et al. 10.3390/drones6120422
27. Technologies and Innovative Methods for Precision Viticulture: A Comprehensive Review M. Ferro & P. Catania 10.3390/horticulturae9030399
28. Sentinel-2 Validation for Spatial Variability Assessment in Overhead Trellis System Viticulture Versus UAV and Agronomic Data S. Di Gennaro et al. 10.3390/rs11212573
29. FANETs in Agriculture - A routing protocol survey G. Kakamoukas et al. 10.1016/j.iot.2020.100183
30. Remote sensing revolutionizing agriculture: Toward a new frontier X. Wang et al. 10.1016/j.future.2024.107691
31. Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine M. Maimaitijiang et al. 10.1016/j.isprsjprs.2017.10.011
32. Beyond the traditional NDVI index as a key factor to mainstream the use of UAV in precision viticulture A. Matese & S. Di Gennaro 10.1038/s41598-021-81652-3
33. Scoping the Field: Recent Advances in Optical Remote Sensing for Precision Viticulture K. Loggenberg et al. 10.3390/ijgi13110385
34. Evaluation of Leaf Area Index (LAI) of Broadacre Crops Using UAS-Based LiDAR Point Clouds and Multispectral Imagery F. Zhang et al. 10.1109/JSTARS.2022.3172491
35. Evaluating Urban Green Spaces Using UAV-Based Green Leaf Index Ş. Akça 10.53093/mephoj.1536466
36. Remote sensing image fusion on 3D scenarios: A review of applications for agriculture and forestry J. Jurado et al. 10.1016/j.jag.2022.102856
37. Performance of an aerially applied liquid Bacillus thuringiensis var. israelensis formulation (strain AM65‐52) against mosquitoes in mixed saltmarsh–mangrove systems and fine‐scale mapping of mangrove canopy cover using affordable drone‐based imagery B. Johnson et al. 10.1002/ps.5933
38. Assessment of vineyard vigour and yield spatio-temporal variability based on UAV high resolution multispectral images M. Ferro et al. 10.1016/j.biosystemseng.2023.06.001
39. The potential for RGB images obtained using unmanned aerial vehicle to assess and predict yield in sugarcane fields G. Sanches et al. 10.1080/01431161.2018.1448484
40. Linear Feature-Based Triangulation for Large-Scale Orthophoto Generation Over Mechanized Agricultural Fields S. Hasheminasab et al. 10.1109/TGRS.2022.3167378
41. UAS, sensors, and data processing in agroforestry: a review towards practical applications L. Pádua et al. 10.1080/01431161.2017.1297548