High-resolution NDVI time series and pixel-wise NDVI–climate correlations across Spain's National Parks (1984–2023)

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Authors: Magí Franquesa, Adell-Michavila, Maria, Sergio Martín Vicente-Serrano
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Abstract

This repository accompanies the study "Vegetation sensitivity to interannual climate variability in Spain's National Parks: seasonal patterns and accumulation timescales" and provides the complete set of pixel-wise correlation results between vegetation activity and climate variables across Spain's National Park Network. The dataset includes monthly Pearson correlation coefficients between NDVI (and kNDVI) and precipitation, maximum temperature (Tmax), minimum temperature (Tmin), and the Standardized Precipitation–Evapotranspiration Index (SPEI), computed for multiple accumulation time scales (1, 3, 6, 9, and 12 months), together with their p- values, the number of valid years per pixel, and Spearman rank correlations for a 5 % subsample of pixels. All correlations were calculated using detrended time series and are based on interannual variability for each calendar month over the 1984–2023 period. In addition, the repository includes the monthly NDVI time series used in the analysis. These NDVI data were originally generated and described in Franquesa et al. (2025) from Landsat 5, 7, and 8 imagery and are redistributed here to support reproducibility and further analyses. All outputs are provided as NetCDF files at 30 m spatial resolution, consistent with the underlying Landsat-based NDVI dataset. This spatial detail enables analyses at the scale of individual national parks or specific vegetation types, complementing the aggregated results presented in the associated manuscript. Version 2.0 supersedes version 1, in which the detrending step left series with missing years undetrended and significance was assessed without control of the false discovery rate. Both issues are corrected in this version, which also adds the number of valid years, Spearman correlations and the kNDVI results. The NDVI time series are unchanged. All results in the associated manuscript are based on this version.

Fields of Study & Subjects

Remote Sensing in Agriculture Hydrology and Drought Analysis Plant Water Relations and Carbon Dynamics

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 February 2026
Document type
Dataset