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).

本数据集包含多源辅助变量集合，用于支撑森林监测与模型开发工作。本数据集整合了哨兵二号（Sentinel-2）、陆地卫星（Landsat）遥感数据及其衍生产品，实现了覆盖七个欧洲国家的全域一致覆盖。数据集包含通过先进合成与时间序列处理方法生成的光谱类与变化相关预测变量。本数据集并未直接提供森林变化图，而是提供经过统一标准化的卫星遥感预测变量，可直接用于模型训练、验证与分析工作。其应用场景涵盖森林动态评估、生物量估算、冠层恢复监测、生物多样性保护、碳通量追踪以及气候变化影响研究等。

受存储空间限制，本次仅提供2023年陆地卫星（Landsat）多光谱数据、2023年哨兵二号（Sentinel-2）数据以及变化指标相关数据。其余数据集可按需申请获取，包括2017-2024年哨兵一号（Sentinel-1）多时序数据、哥白尼计划（Copernicus）相关产品（如森林类型数据、森林掩膜数据与地形数据），以及2017-2023年哨兵二号（Sentinel-2）与1984-2023年陆地卫星（Landsat）的多时序数据。