Fractional land cover maps for the European Alps

This repository contains annual fractional land cover maps for the European Alps covering the period 1986–2023. The dataset is organized by land cover class. For each class, one multi-band raster is provided, where each band corresponds to one year in the time series and stores the fractional land cover of that class for the respective year. The three classes included are tree cover, grassland, and bare ground, with values ranging from 0 to 100%. The dataset is derived from dense Earth observation time series based on Landsat 4–8 and Sentinel-2A/B imagery. It provides continuous sub-pixel estimates of land cover composition and is designed to capture gradual changes in vegetation and land surface composition over time. This makes it particularly useful for studying long-term vegetation dynamics, forest disturbance and recovery, and land cover change in heterogeneous mountain landscapes such as the European Alps. These fractional land cover maps were used in the analysis presented in Mandl et al. (2024), Remote Sensing of Environment, 308, 114194 (https://doi.org/10.1016/j.rse.2024.114194), titled “Unmixing-based forest recovery indicators for predicting long-term recovery success” and Mandl et al. (2026), Agricultural and Forest Meteorology 378 (https://doi.org/10.1016/j.agrformet.2026.111016, titled "The role of thermal constraints in post-disturbance forest recovery across the European Alps – a large-scale remote sensing study" The studies uses fractional cover maps derived from spectral unmixing as the basis for ecologically interpretable indicators of forest recovery.本仓库收录覆盖1986–2023年时段的欧洲阿尔卑斯山区年度分率土地覆盖（fractional land cover）图。该数据集按土地覆盖类别进行组织，每一类均对应一张多波段栅格（multi-band raster）数据，其中每个波段对应时间序列中的一个年份，存储对应年份该类别的土地覆盖占比。本次数据集涵盖三类土地覆盖类型：乔木覆盖、草地与裸地，数值取值范围为0至100%。 本数据集基于Landsat 4–8及Sentinel-2A/B影像构建的密集地球观测（Earth observation）时间序列生成，可提供土地覆盖组成的连续亚像元估算结果，旨在捕捉植被与地表组成随时间发生的渐进式变化。该特性使其特别适用于研究长期植被动态、森林扰动与恢复过程，以及欧洲阿尔卑斯等异质性山地景观中的土地覆盖变化。 上述分率土地覆盖图已应用于两项已发表研究：其一为Mandl等人（2024）发表于《环境遥感（Remote Sensing of Environment）》第308卷的论文（论文编号114194，DOI: https://doi.org/10.1016/j.rse.2024.114194），题为《基于解混的森林恢复指标用于预测长期恢复成功率》；其二为Mandl等人（2026）发表于《农业与森林气象学（Agricultural and Forest Meteorology）》第378卷的论文（DOI: https://doi.org/10.1016/j.agrformet.2026.111016），题为《热约束在欧洲阿尔卑斯山扰动后森林恢复中的作用——一项大规模遥感研究》。 上述两项研究均以通过光谱解混（spectral unmixing）得到的分率覆盖图为基础，构建了可用于生态学解释的森林恢复指标。