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MUSES Leaf Area Index (LAI) 8-Day Global 250m SIN Grid in 2010

Name: MUSES Leaf Area Index (LAI) 8-Day Global 250m SIN Grid in 2010
Creator: Xiao Zhiqiang
Keywords: 2. Zero hunger, Vegetation, MUSES, 13. Climate action, 15. Life on land, Remote sensing, LAI

Research datakeyboard_double_arrow_right Dataset 27 Mar 2023Publisher:Zenodo

Authors: Xiao Zhiqiang;

doi: 10.5281/zenodo.7772736 , 10.5281/zenodo.7772737

MUSES Leaf Area Index (LAI) 8-Day Global 250m SIN Grid in 2010

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Abstract

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/). This dataset is the MUSES global LAI product at 250m spatial resolution and 8-day temporal resolution. The MUSES LAI product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from time-series Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product using general regression neural networks (GRNNs) (Xiao et al., 2022; Xiao et al., 2014; Xiao et al., 2016). This dataset is the MUSES LAI product in 2010. Please click here to download the MUSES LAI product in 2009 and click here to download the MUSES LAI product in 2011. Dataset Characteristics: Spatial Coverage: Global Temporal Coverage: 2010 Spatial Resolution: 250m Temporal Resolution: 8 days Projection: Sinusoidal Data Format: HDF Scale: 0.1 Valid Range: 0 – 100 Citation (Please cite this paper whenever these data are used): 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. 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. 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. 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).

Keywords

Vegetation, MUSES, Remote sensing, LAI

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