Remote and Proximal Sensing-Derived Spectral Indices and Biophysical Variables for Spatial Variation Determination in Vineyards

Remote-sensing measurements are crucial for smart-farming applications, crop monitoring, and yield forecasting, especially in fields characterized by high heterogeneity. Therefore, in this study, Precision Viticulture (PV) methods using proximal- and remote-sensing technologies were exploited and co...

Full description

Saved in:
Bibliographic Details
Published in:Agronomy (Basel) 2021-04, Vol.11 (4), p.741
Main Authors: Darra, Nicoleta, Psomiadis, Emmanouil, Kasimati, Aikaterini, Anastasiou, Achilleas, Anastasiou, Evangelos, Fountas, Spyros
Format: Article
Language:English
Subjects:
Agricultural production
Agriculture
Condition monitoring
crop circle ACS-470
Crops
Digital agriculture
Heterogeneity
Mathematical analysis
Normalized difference vegetative index
precision viticulture
Productivity
Radiation
Remote sensing
Satellite imagery
Satellites
Sensors
Sentinel-2
Spatial variations
Unmanned aerial vehicles
Vegetation
vegetation biophysical variables
Vegetation cover
Vegetation index
vegetation indices
Vineyards
Viticulture
Wineries & vineyards
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Remote-sensing measurements are crucial for smart-farming applications, crop monitoring, and yield forecasting, especially in fields characterized by high heterogeneity. Therefore, in this study, Precision Viticulture (PV) methods using proximal- and remote-sensing technologies were exploited and compared in a table grape vineyard to monitor and evaluate the spatial variation of selected vegetation indices and biophysical variables throughout selected phenological stages (multi-seasonal data), from veraison to harvest. The Normalized Difference Vegetation Index and the Normalized Difference Red-Edge Index were calculated by utilizing satellite imagery (Sentinel-2) and proximal sensing (active crop canopy sensor Crop Circle ACS-470) to assess the correlation between the outputs of the different sensing methods. Moreover, numerous vegetation indices and vegetation biophysical variables (VBVs), such as the Modified Soil Adjusted Vegetation Index, the Normalized Difference Water Index, the Fraction of Vegetation Cover, and the Fraction of Absorbed Photosynthetically Active Radiation, were calculated, using the satellite data. The vegetation indices analysis revealed different degrees of correlation when using diverse sensing methods, various measurement dates, and different parts of the cultivation. The results revealed the usefulness of proximal- and remote-sensing-derived vegetation indices and variables and especially of Normalized Difference Vegetation Index and Fraction of Absorbed Photosynthetically Active Radiation in the monitoring of vineyard condition and yield examining, since they were demonstrated to have a very high degree of correlation (coefficient of determination was 0.87). The adequate correlation of the vegetation indices with the yield during the latter part of the veraison stage provides valuable information for the future estimation of production in broader areas.
ISSN:2073-4395
2073-4395
DOI:10.3390/agronomy11040741