Benchmarking the Reliability of Sentinel-2 Satellite Data for Estimating Vineyard NDVI and Leaf Area Index Parameters through UAV LiDAR and Multispectral Imagery
Author:
Affiliation:
1. Information Technology Group, Wageningen University & Research, 6708 PB Wageningen, The Netherlands
Publisher
MDPI
Link
https://www.mdpi.com/2673-4931/29/1/1/pdf
Reference21 articles.
1. Giovos, R., Tassopoulos, D., Kalivas, D., Lougkos, N., and Priovolou, A. (2021). Remote Sensing Vegetation Indices in Viticulture: A Critical Review. Agriculture, 11.
2. Mapping the Spatial Variability of Botrytis Bunch Rot Risk in Vineyards Using UAV Multispectral Imagery;Valente;Eur. J. Agron.,2023
3. Agronomic Classification between Vineyards (‘Verdejo’) Using NDVI and Sentinel-2 and Evaluation of Their Wines;Rubio;VITIS-J. Grapevine Res.,2019
4. Sun, L., Gao, F., Anderson, M., Kustas, W., Alsina, M., Sanchez, L., Sams, B., McKee, L., Dulaney, W., and White, W. (2017). Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards. Remote Sens., 9.
5. Vélez, S., Vacas, R., Martín, H., Ruano-Rosa, D., and Álvarez, S. (2022). A Novel Technique Using Planar Area and Ground Shadows Calculated from UAV RGB Imagery to Estimate Pistachio Tree (Pistacia vera L.) Canopy Volume. Remote Sens., 14.
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