European NDVI-derived Phenology Dataset (1982–2022): Metrics, Variability and Trends

This dataset contains 82 raster files (GeoTIFF) and 1 tabular file (CSV) representing the phenological dynamics of the European continent from 1982 to 2022. The products are derived from the PKU GIMMS NDVI v1.2 dataset (Li et al., 2023) and have been processed to support long-term environmental monitoring and climate change impact studies at a continental scale.

📦 Included Data Products

The dataset is organized into the following components:

Long-term Monthly Mean NDVI (1982–2022): 12 GeoTIFFs representing the average vegetation greenness for each calendar month over 41 years.

Decadal Monthly Mean NDVI: 48 GeoTIFFs (12 months × 4 decades) capturing the evolution of monthly NDVI across four periods (1982–1992, 1993–2002, 2003–2012, 2013–2022).

Phenological Clusters Map (k=5): 1 GeoTIFF providing a spatial classification of Europe into 5 distinct eco-phenological regions based on NDVI seasonality.

Land Surface Phenology (LSP) Metrics: 16 GeoTIFFs (4 metrics × 4 decades) for Start of Season (SOS), Peak of Season (POS), End of Season (EOS), and Length of Season (LOS).

Inter-Decadal Phenological Shifts: 4 GeoTIFFs showing the pixel-wise shifts in SOS, POS, EOS, and LOS between the first and last decades.

Phenology Variability Index (PVI): 1 GeoTIFF quantifying the interannual stability/variability of phenological timing.

Trend Analysis Results: 1 CSV file containing cluster-aggregated Mann–Kendall and Theil–Sen statistics for monthly NDVI trends (1982–2022).

🛠 Technical Specifications

Spatial Resolution: 0.0833° (~8 km)

Temporal Coverage: 1982–2022

Coordinate Reference System: WGS84 (EPSG:4326)

Format: GeoTIFF (.tif) and Comma-Separated Values (.csv)

Study Area: Southern and Central Europe (10° W – 28° E; 35° N – 50° N)

📂 Access & Citation

Main Reference: Samela, C., Imbrenda, V., Coluzzi, R., & Lanfredi, M. (2026). Four decades of vegetation phenology across Europe using PKU GIMMS NDVI: assessing timing, stability and spatial patterns. International Journal of Applied Earth Observation and Geoinformation, 146, 105041. https://doi.org/10.1016/j.jag.2025.105041