MUSES Leaf Area Index (LAI) Monthly Global 1km SIN Grid in 2006

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 1 km spatial resolution and monthly 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., 2014; Xiao et al., 2016). The MUSES LAI product is spatially complete and temporally continuous.

This dataset is the MUSES LAI product in 2006. Please click here to download the MUSES LAI product in 2005, and click here to download the MUSES LAI product in 2007.

Dataset Characteristics:

Spatial Coverage: Global

Temporal Coverage: 2006

Spatial Resolution: 1 km

Temporal Resolution: 1 month

Projection: Sinusoidal

Data Format: HDF

Scale: 0.01

Valid Range: 0 – 1000

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

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, 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. (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 ([e-mail]).

多尺度卫星遥感（MUltiscale Satellite remotE Sensing，简称MUSES）产品套件包含针对归一化植被指数（Normalized Difference Vegetation Index, NDVI）、植被近红外反射率（Near-Infrared Reflectance of Vegetation, NIRv）、叶面积指数（Leaf Area Index, LAI）、吸收光合有效辐射比例（Fraction of Absorbed Photosynthetically Active Radiation, FAPAR）、植被覆盖度（Fractional Vegetation Coverage, FVC）、总初级生产力（Gross Primary Production, GPP）、净初级生产力（Net Primary Production, NPP）等参数的不同时空分辨率产品。如需了解MUSES产品的更多信息，请访问该网站：https://muses.bnu.edu.cn/。

本数据集为空间分辨率1km、时间分辨率月尺度的MUSES全球叶面积指数（LAI）产品。MUSES LAI产品采用正弦格网投影，时间跨度为2000年至2019年（持续更新中），其基于时间序列中等分辨率成像光谱仪（Moderate Resolution Imaging Spectroradiometer, MODIS）地表反射率产品，通过广义回归神经网络（General Regression Neural Networks, GRNNs）生成（Xiao等，2014；Xiao等，2016）。该产品空间全覆盖且时间序列连续。

本数据集为2006年版MUSES LAI产品。请点击此处下载2005年版MUSES LAI产品，点击此处下载2007年版MUSES LAI产品。

数据集特性：
空间覆盖范围：全球
时间覆盖范围：2006年
空间分辨率：1 km
时间分辨率：1个月
投影方式：正弦格网
数据格式：HDF
缩放系数：0.01
有效取值范围：0 – 1000

引用说明（使用该数据时请务必引用以下文献）：
1. 肖志强等（2014）. 利用广义回归神经网络从时间序列MODIS地表反射率生成GLASS叶面积指数产品. IEEE地球科学与遥感汇刊, 52, 209-223.
2. 肖志强等（2016）. 基于MODIS与AVHRR地表反射率的长时序全球陆表卫星叶面积指数产品. IEEE地球科学与遥感汇刊, 54, 5301-5318.
3. 肖志强, 宋金玲, 杨桦, 孙睿, 李娟.（2022）. 基于MODIS地表反射率数据的250m分辨率全球叶面积指数产品. 国际遥感学报, 43(4), 1199-1225.
4. 肖志强等（2017）. 四种长时序全球叶面积指数产品的评估. 农业与森林气象, 246, 218-230.

如有任何疑问，请联系肖志强教授（[e-mail]）。