Multispectral imagery and GIS data from an Unmanned Aerial Vehicle (UAV) were used to identify vineyard rows and segment canopies in the Okanagan region. The dataset includes high-resolution imagery with a 3cm ground pixel size, processed vegetation indices (NDRE, GNDVI), and a canopy height model. Author Kelvin Boateng contributed this dataset to the Borealis Harvested Dataverse, with a last update recorded on 2026-05-02.
Use Cases
- Train models for vineyard row identification based on the described rule-based geometric clustering approach.
- Analyze spatial patterns of vine vigour based on the provided NDRE and GNDVI vegetation indices.
- Develop segmentation workflows for canopy delineation based on the generated canopy height model and 0.5m threshold.
- Quantify intra-vineyard variability for data-driven management based on the extracted zonal statistics and canopy area metrics.
Strengths
- High-resolution multispectral imagery with a ground pixel size of 3cm.
- Includes specific vegetation index ranges (e.g., NDRE from 0.13 to 0.65) and canopy area statistics (0.01–20.42 square meters).
- Workflow produced continuous and geometrically consistent row networks for reliable statistical extraction.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Data may reflect geographic bias inherent to the single Okanagan region study area.
Provenance
- Source
- Borealis Harvested Dataverse
- Collection Method
- Multispectral data obtained from a UAV and processed with GIS-based spatial analysis approaches.
- Time Range
- null
- Freshness
- Last updated 2026-05-02 04:10:41; freshness should be verified.
- Geography
- Okanagan region