2000-2020 LAI data and variable data

This dataset contains seven key variables used to model Leaf Area Index (LAI) dynamics across mainland China (0.1° resolution, 2000–2020), selected through rigorous multicollinearity analysis (VIF < 10). The variables capture climatic, topographic, and anthropogenic drivers:
Precipitation (Pre): Annual cumulative precipitation (mm), sourced from the 1-km Monthly Precipitation Dataset for China (Tibetan Plateau Data Center). Highlights water availability constraints on vegetation.
Temperature (Tmp): Annual mean temperature (°C), derived from the same source. Reflects thermal controls on plant growth.
Digital Elevation Model (DEM): Elevation (m) from SRTM V4.1, with slope/aspect calculated to assess topographic effects.
Forest Fragmentation Index (FFI): Quantifies landscape connectivity loss (range: 0–1), computed from annual land cover data (CLCD). Critical for evaluating human-induced habitat degradation.
Nighttime Light (Light): Harmonized DMSP-OLS/SNPP-VIIRS composites, proxy for urbanization pressure.
Slope (Slope): Terrain steepness (°), derived from DEM. Influences water retention and anthropogenic accessibility.
Aspect (Aspect): Terrain orientation (categorical), included for microclimatic effects (e.g., solar exposure).
They all resampled to 0.1° grid (WGS1984) and clipped to China’s boundaries.