NDVI prediction dataset for the Qinghai-Tibet Plateau based on CMIP6 (2025–2100)

This dataset is developed based on three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), in conjunction with 1 km resolution historical temperature, precipitation, and NDVI data from 2000 to 2020 across the Qinghai-Tibet Plateau. A multiple linear regression model was employed to simulate the relationship between climate factors and vegetation response, enabling annual NDVI prediction from 2025 to 2100. To enhance spatial accuracy, climate model outputs were downscaled using bias correction and bilinear interpolation techniques. All processing and modeling tasks, including simulation and error control, were performed using MATLAB, with masking applied to non-vegetation areas such as glaciers and water bodies. The dataset spans 76 years, covers the entire Qinghai-Tibet Plateau, has a spatial resolution of 1 km, and consists of 228 GeoTIFF raster files with a total volume of 5.65 GB. Model accuracy was evaluated using the coefficient of determination (R²) and root mean square error (RMSE), with all R² values exceeding 0.72 and RMSE values controlled below 0.13, demonstrating high reliability. This dataset features multi-scenario comparability, long-term temporal continuity, and high spatial detail, making it valuable for studies on ecosystem services simulation, regional carbon sink assessment, and vegetation dynamics under climate change scenarios.