MUSES Leaf Area Index (LAI) Derived from MODIS Data 8-Day Global 0.05º Geographic Grid Since 2000

The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/).

The MUSES LAI product at 0.05º spatial resolution and 8-day temporal resolution was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs)  (Xiao et al., 2014; Xiao et al., 2016). It is provided on Geographic grid and spans from 2000 to 2023 (continuously updated). The MUSES LAI product is spatially complete and temporally continuous.

Dataset Characteristics:

• Spatial Coverage: 180º W – 180º E, 90º S – 90º N
• Temporal Coverage: 2000 – 2023
• Spatial Resolution: 0.05º (approximately 5 km)
• Temporal Resolution: 8 days
• Projection: Geographic
• Data Format: HDF
• Scale: 0.01
• Valid Range: 0 – 1000

Citation (Please cite this paper whenever these data are used):

1. Xiao Zhiqiang, Jinling Song, Hua Yang, Rui Sun and Juan Li. (2022). A 250 m resolution global leaf area index product derived from MODIS surface reflectance data. International Journal of Remote Sensing, 43(4), 1199-1225.
2. Xiao Zhiqiang, et al. (2014). Use of General Regression Neural Networks for Generating the GLASS Leaf Area Index Product From Time-Series MODIS Surface Reflectance. IEEE Transactions on Geoscience and Remote Sensing, 52, 209-223.
3. Xiao Zhiqiang, et al. (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, 5301-5318.
4. Xiao Zhiqiang, et al. (2017). Evaluation of four long time-series global leaf area index products. Agricultural and Forest Meteorology, 246, 218-230.

If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).