2000-2020 LAI data and variable data
<p dir="ltr">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 d...
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| الملخص: | <p dir="ltr">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:</p><p dir="ltr">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.</p><p dir="ltr">Temperature (Tmp): Annual mean temperature (°C), derived from the same source. Reflects thermal controls on plant growth.</p><p dir="ltr">Digital Elevation Model (DEM): Elevation (m) from SRTM V4.1, with slope/aspect calculated to assess topographic effects.</p><p dir="ltr">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.</p><p dir="ltr">Nighttime Light (Light): Harmonized DMSP-OLS/SNPP-VIIRS composites, proxy for urbanization pressure.</p><p dir="ltr">Slope (Slope): Terrain steepness (°), derived from DEM. Influences water retention and anthropogenic accessibility.</p><p dir="ltr">Aspect (Aspect): Terrain orientation (categorical), included for microclimatic effects (e.g., solar exposure).</p><p dir="ltr">They all resampled to 0.1° grid (WGS1984) and clipped to China’s boundaries.</p><p><br></p> |
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