Dataset List


Data Details

MODIS Global Leaf Area Index Product Reprocessing Dataset (2001-2021)

LIU Li1ZHANG Yinghui*2HU Zhongwen*2GAO Xing3WANG Jingzhe4WU Guofeng2
1 Guangdong Polytechnic of Industry & Commerce,Guangzhou 510510,China2 MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area,Shenzhen University,Shenzhen 518060,China3 LREIS Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China4 School of Artificial Intelligence Shenzhen Polytechnic,Shenzhen 518055,China


Published:Oct. 2023

Visitors:1750       Data Files Downloaded:104      
Data Downloaded:83493.18 MB      Citations:

Key Words:

MODIS,Leaf area index,Global Change,spatial-temporal


Based on the MODIS leaf area index (LAI) products, the authors designed an algorithm with maximum fraction of absorbed photosynthetically active radiation in a day to recompile a new reprocessing dataset, in which the vegetation types were input to the model for the LAI analysis. The resolution of the dataset were changed from 500 m to 0.05°. By validation with 280 public measured LAI test sites, the square of the linear fitting correlation coefficient of the reprocessing dataset reaches 0.748. The dataset includes 8-day, monthly, and yearly global LAI with resolution of 0.05°. The scale factor is 0.1. The dataset is archived in .tif format, and consists of 1239 data files with data size of 29.9 GB (Compressed into three files with 2.48 GB).

Foundation Item:

National Natural Science Foundation of China (42201347); China Postdoctoral Science Foundation (2022M712163); Guangdong Province (2021A1515110910, 2023A1515011273); Chinese Academy of Sciences (XDA23090503); Shenzhen (JCYJ20220818101617037, 20220811173316001)

Data Citation:

LIU Li, ZHANG Yinghui*, HU Zhongwen*, GAO Xing, WANG Jingzhe, WU Guofeng. MODIS Global Leaf Area Index Product Reprocessing Dataset (2001-2021)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023.


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     [4] GCOS. The Global Observing System For Climate Implementation Needs [R], 2016.
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     [9] Zhang, Y., Hu, Z., Wang, J., et al. Temporal upscaling of MODIS instantaneous FAPAR improves forest gross primary productivity (GPP) simulation [J]. International Journal of Applied Earth Observation and Geoinformation, 2023, 121.
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Data Product:

ID Data Name Data Size Operation
1 8-Day_LAI_2001_2010.rar 961743.10KB
2 8-Day_LAI_2011_2021.rar 1078138.67KB
3 Monthly_Yearly_LAI_2001_2021.rar 565512.28KB