LAI dataset from multiple products (MOD15A2H/GIMMS LAI4g/GLOBMAP LAI V3/GLASS-AVHRR/GLASS-MODIS/HIQ/GEOV2) for the Tibetan Plateau – Data supporting "How Consistent Are Satellite LAI Products in Characterizing Vegetation Dynamics Over the Tibetan Plateau?" (under review)

This dataset supports the manuscript "How Consistent Are Satellite LAI Products in Characterizing Vegetation Dynamics Over the Tibetan Plateau?"(under review). **Data content** The dataset contains annual growing‑season (May to October) mean Leaf Area Index (LAI) for seven publicly available satellite LAI products over the Tibetan Plateau (TP) for the period 2001–2018. The products are: - MOD15A2H - GIMMS LAI4g - GLOBMAP LAI V3 - GLASS‑AVHRR - GLASS‑MODIS - HIQ - GEOV2 Non‑vegetated areas have been masked out. **Processing steps** 1. All products were harmonised to the common period 2001–2018. 2. For each product, the growing season (May–October) mean LAI was calculated annually following Shen et al. (2022). 3. All data were resampled to a common spatial grid of 0.1° × 0.1° using the nearest‑neighbour method. **File organisation** The data are organised in separate folders by product. Inside each folder, GeoTIFF files are named by year (e.g., 2001.tif, 2002.tif, …). Each GeoTIFF file represents the growing‑season mean LAI for that product and year, covering the Tibetan Plateau extent with non‑vegetated areas masked out. **Original data sources** - MOD15A2H LAI: https://www.earthdata.nasa.gov/data/ - GIMMS LAI4g: https://zenodo.org/records/8281930 - GLOBMAP LAI V3: https://zenodo.org/records/12698637 - GLASS‑AVHRR LAI and GLASS‑MODIS LAI: https://glass.hku.hk/ - HIQ LAI: https://doi.org/10.5281/zenodo.8296768 - GEOV2 LAI: https://land.copernicus.eu/en/products/vegetation/leaf-area-index-v2-0-1km#general_info - Tibetan Plateau boundary: Resource and Environment Science Data Center (https://www.resdc.cn/) **Citation (this dataset)** If you use these data, please cite this Zenodo dataset: - DOI: 10.5281/zenodo.xxxxxx (to be assigned upon publication) **References** - Myneni, R., Y. Knyazikhin and T. Park (2015). MYD15A2H MODIS/Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006. NASA Land Processes Distributed Active Archive Center. - Myneni, R., Y. Knyazikhin and T. Park. 2021. "MODIS/terra leaf area index/FPAR 8-day L4 global 500m SIN grid V061." NASA EOSDIS Land Processes Distributed Active Archive Center (DAAC) data set: MOD15A12H. 061. https://doi.org/10.5067/MODIS/MOD15A2H.061 - Cao, S., M. Li, Z. Zhu, Z. Wang, J. Zha, W. Zhao, Z. Duanmu, J. Chen, Y. Zheng, Y. Chen, R. B. Myneni and S. Piao. 2023. "Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020." Earth System Science Data 15(11): 4877–4899. https://doi.org/10.5194/essd-15-4877-2023. - Liu, Y., R. Liu and J. M. Chen. 2012. "Retrospective retrieval of long‑term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data." Journal of Geophysical Research: Biogeosciences 117(G4). https://doi.org/10.1029/2012jg002084. - Xiao, Z., S. Liang, J. Wang, Y. Xiang, X. Zhao and J. Song. 2016. "Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived From MODIS and AVHRR Surface Reflectance." IEEE Transactions on Geoscience and Remote Sensing 54(9): 5301–5318. https://doi.org/10.1109/tgrs.2016.2560522. - Ma, H. and S. Liang. 2022. "Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model." Remote Sensing of Environment 273. https://doi.org/10.1016/j.rse.2022.112985. - Baret, F., M. Weiss, R. Lacaze, F. Camacho, H. Makhmara, P. Pacholcyzk and B. Smets. 2013. "GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production." Remote Sensing of Environment 137: 299–309. https://doi.org/10.1016/j.rse.2012.12.027. - Verger, A., F. Baret and M. Weiss (2013). GEOV2/VGT: near real time estimation of global biophysical variables from VEGETATION-P data. MultiTemp 2013: 7th International Workshop on the Analysis of Multi-temporal Remote Sensing Images. - Yan, K., J. Wang, R. Peng, K. Yang, X. Chen, G. Yin, J. Dong, M. Weiss, J. Pu and R. B. Myneni. 2024. "HiQ-LAI: a high-quality reprocessed MODIS leaf area index dataset with better spatiotemporal consistency from 2000 to 2022." Earth System Science Data 16(3): 1601–1622. https://doi.org/10.5194/essd-16-1601-2024. - Shen, M., S. Wang, N. Jiang, J. Sun, R. Cao, X. Ling, B. Fang, L. Zhang, L. Zhang, X. Xu, W. Lv, B. Li, Q. Sun, F. Meng, Y. Jiang, T. Dorji, Y. Fu, A. Iler, Y. Vitasse, H. Steltzer, Z. Ji, W. Zhao, S. Piao and B. Fu. 2022. "Plant phenology changes and drivers on the Qinghai–Tibetan Plateau." Nature Reviews Earth & Environment 3(10): 633–651. https://doi.org/10.1038/s43017-022-00317-5. **License** This dataset is released under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. This dataset supports the manuscript "How Consistent Are Satellite LAI Products in Characterizing Vegetation Dynamics Over the Tibetan Plateau?". **Data content** The dataset contains annual growing‑season (May to October) mean Leaf Area Index (LAI) for seven publicly available satellite LAI products over the Tibetan Plateau (TP) for the period 2001–2018. The products are: - MOD15A2H - GIMMS LAI4g - GLOBMAP LAI V3 - GLASS‑AVHRR - GLASS‑MODIS - HIQ - GEOV2 Non‑vegetated areas have been masked out. **Processing steps** 1. All products were harmonised to the common period 2001–2018. 2. For each product, the growing season (May–October) mean LAI was calculated annually following Shen et al. (2022). 3. All data were resampled to a common spatial grid of 0.1° × 0.1° using the nearest‑neighbour method. **File organisation** The data are organised in separate folders by product. Inside each folder, GeoTIFF files are named by year (e.g., 2001.tif, 2002.tif, …). Each GeoTIFF file represents the growing‑season mean LAI for that product and year, covering the Tibetan Plateau extent with non‑vegetated areas masked out. **Original data sources**- MOD15A2H LAI (Myneni et al., 2015, 2021): https://www.earthdata.nasa.gov/data/- GIMMS LAI4g (Cao et al., 2023): https://zenodo.org/records/8281930- GLOBMAP LAI V3 (Liu et al., 2012): https://zenodo.org/records/12698637- GLASS‑AVHRR LAI and GLASS‑MODIS LAI (Xiao et al., 2016; Ma & Liang, 2022): https://glass.hku.hk/- HIQ LAI (Yan et al., 2024): https://doi.org/10.5281/zenodo.8296768- GEOV2 LAI (Baret et al., 2013; Verger et al., 2013): https://land.copernicus.eu/en/products/vegetation/leaf-area-index-v2-0-1km#general_info- Tibetan Plateau boundary: Resource and Environment Science Data Center (https://www.resdc.cn/) **Citation (this dataset)** If you use these data, please cite this Zenodo dataset: - DOI: 10.5281/zenodo.20091684 **References** - Shen, M., S. Wang, N. Jiang, J. Sun, R. Cao, X. Ling, B. Fang, L. Zhang, L. Zhang, X. Xu, W. Lv, B. Li, Q. Sun, F. Meng, Y. Jiang, T. Dorji, Y. Fu, A. Iler, Y. Vitasse, H. Steltzer, Z. Ji, W. Zhao, S. Piao and B. Fu. 2022. "Plant phenology changes and drivers on the Qinghai–Tibetan Plateau." Nature Reviews Earth & Environment 3(10): 633–651. https://doi.org/10.1038/s43017-022-00317-5.