A simple features data frame with a sample of vineyards in Italy in 2020. The data describe several spatial and management features of a random sample of 3,686 vineyards distributed throughout Italy. Vineyards are represented by their centroids, and the characteristics were assessed by means of GIS-supported geospatial analysis.
Usage
data(vineyards)Format
A data frame with 3,686, rows and 11 variables:
- id
Unique ID of vineyard (centroid)
- row_spacing
Distance between two rows (m)
- training
Categories of trellising and pruning systems used to control a vine's shape. The first category is vertical training systems, such as Sylvoz, Guyot, Geneva Double Curtain (GDC) and Free-cordon (FC), and is designated as “VS”. The second category (“HS”) includes the horizontal training systems, such as Tendone, Pergola and other local systems. The last category consists of the traditional Alberello training system, also known as Goblet or Bush vine, and is designated as “A”.
- lw_ratio
Ratio between the length of the rows and the width of the vineyard; an indicator of management efficiency that relates to agricultural machinery transit and maneuvering
- headland_size
Width of the operational headland (m); sufficiently wide headlands along the vineyard enable turning equipment and may contribute to biodiversity conservation
- block_shape
Shape of the vineyar, classified as regular (designated as “R”) and irregular (designated as “I”); block shape is informative about mechanization propensity
- mean_slope
Average percentage of inclination of the block relative to the horizontal plane
- max_slope
Maximum percentage of inclination of the block relative to the horizontal plane
- NAME_LATN
Name of region in Latin script
- NUTS_ID
NUTS-2 identifier of region
- geometry
Geometry of vineyard centroids
Source
Cogato, Alessia, et al. "A sample of Italian vineyards: Landscape and management parameters dataset." Data in brief 33 (2020): 106589. doi:10.1016/j.dib.2020.106589