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Mean NDVI Values (1982-2018) and Future Predictions Using CHELSA Bioclim Variables for Türkiye

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/13147272
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This dataset contains mean Normalized Difference Vegetation Index (NDVI) values from 1982 to 2018 and their future predictions based on CHELSA bioclimatic variables, specifically for the region of Türkiye. The data is provided in .asc format and includes both historical and projected NDVI values under different climate scenarios. Contents: Historical NDVI Data (1982-2018): Mean NDVI values derived from remote sensing data. Future NDVI Predictions: NDVI projections for the periods 2011-2040, 2041-2070, and 2071-2100 under three Shared Socioeconomic Pathways (SSPs): SSP1-2.6, SSP3-7.0, and SSP5-8.5. Methodology: Model Training: A Random Forest Regressor was used to model the relationship between NDVI and the selected bioclim variables. The model achieved an R² of 0.9341, Mean Absolute Error of 0.0275, and Root Mean Squared Error of 0.0499. Future Predictions: Future NDVI values were predicted using the trained model and future CHELSA bioclim projections. Predictions were made for three future periods (2011-2040, 2041-2070, 2071-2100) under three SSPs (SSP1-2.6, SSP3-7.0, SSP5-8.5). Data Specifications: Extent: Covers the geographical area of Türkiye and adjacents. Sources: NDVI Data: Ma, Z., Dong, C., Lin, K., Yan, Y., Luo, J., Jiang, D., & Chen, X. (2022). A Global 250-m Downscaled NDVI Product from 1982 to 2018. Remote Sensing, 14(15), 3639. CHELSA Bioclim Data: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017). Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122 Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, H.P., Kessler, M. Data from: Climatologies at high resolution for the earth’s land surface areas. Dryad Digital Repository. http://dx.doi.org/doi:10.5061/dryad.kd1d4
创建时间:
2024-08-04
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