Multi-source remote sensing data for forest monitoring

This dataset provides a multi-source collection of auxiliary variables to support forest monitoring and model development. It integrates remote sensing data from Sentinel-2, Landsat, and derived products, delivering consistent wall-to-wall coverage across seven European countries. The dataset includes spectral and change-related predictors derived through advanced compositing and time-series processing methods. Rather than offering direct forest change maps, it supplies harmonized satellite-based predictors that can be readily used for model training, validation, and analysis. Applications include assessing forest dynamics, estimating biomass, monitoring canopy recovery, conserving biodiversity, tracking carbon, and researching the impacts of climate change.

Due to space constraints, only Landsat multispectral data for 2023, Sentinel-2 data for 2023, and data related to change metrics are provided. Additional datasets are available upon request, including Sentinel-1 multitemporal data (2017-2024), Copernicus-related products such as forest type, forest mask, and terrain data, as well as multitemporal data from both Sentinel-2 (2017-2023) and Landsat (1984-2023).