Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment

Sentinel-2 (S2) is widely considered a reliable satellite constellation for monitoring several crops, such as grapevine (Vitis vinifera L.). A large dataset of Italian vineyards randomly chosen was monitored with S2 from 2017 to 2022. Two vegetation indices (VIs) and their statistics were calculated from each vineyard. In addition, structural features and topographic information were assessed using Google Earth and national databases. The research study aims to identify the most relevant drivers of spatial variability by assessing the VIs among the whole dataset and the within-vineyard variability. The latitude and the vintage showed the most relevant effect on spatial variability, depicting the effect of daylight hours, climate conditions and weather events. However, the vintage did not affect the patterns of the within-field variability. Regarding grapevine management, training systems and the rows’ orientation were relevant boosters of variability. While the vineyards planted with north–south-oriented rows reached the highest VIs values, the east–west-oriented ones showed the highest variability. Finally, an interaction effect was detected between hill or plain plantation and the terrain slope on both the average and variability of the VIs. The conclusions from the present study suggest the relevance of clustering vineyards under remote supervision according to the structural features to reduce data variability. Further studies should investigate other structural features or managerial properties.

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Publication Details

Journal
AgriEngineering
Published
2024-10-31
DOI
https://doi.org/10.3390/agriengineering6040232
Citations
1
Primary Topic
Horticultural and Viticultural Research
Type
article
Field-Weighted Citation Impact
0.60
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Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment

Diego Tomasi, Alessandro Zanchin, Francesco Marinello, Alessia Cogato et al.
1 citations
AgriEngineering
Horticultural and Viticultural Research
0.60
article

Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment

Diego Tomasi, Alessandro Zanchin, Francesco Marinello, Alessia Cogato, Marco Sozzi
article en
1 citations

Abstract

Sentinel-2 (S2) is widely considered a reliable satellite constellation for monitoring several crops, such as grapevine (Vitis vinifera L.). A large dataset of Italian vineyards randomly chosen was monitored with S2 from 2017 to 2022. Two vegetation indices (VIs) and their statistics were calculated from each vineyard. In addition, structural features and topographic information were assessed using Google Earth and national databases. The research study aims to identify the most relevant drivers of spatial variability by assessing the VIs among the whole dataset and the within-vineyard variability. The latitude and the vintage showed the most relevant effect on spatial variability, depicting the effect of daylight hours, climate conditions and weather events. However, the vintage did not affect the patterns of the within-field variability. Regarding grapevine management, training systems and the rows’ orientation were relevant boosters of variability. While the vineyards planted with north–south-oriented rows reached the highest VIs values, the east–west-oriented ones showed the highest variability. Finally, an interaction effect was detected between hill or plain plantation and the terrain slope on both the average and variability of the VIs. The conclusions from the present study suggest the relevance of clustering vineyards under remote supervision according to the structural features to reduce data variability. Further studies should investigate other structural features or managerial properties.

AgriEngineeringVol. 6(4)
University of Padua (IT)
Climate action
Openalex Percentile: Top 21%
Horticultural and Viticultural Research
0.60
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Satellite Monitoring of Italian Vineyards and Spatio-Temporal Variability Assessment — Diego Tomasi, Alessandro Zanchin, et al. · AgriEngineering (2024) | TGRS Research Map | TGRS