%0 Generic
%A Lin, Wan
%A Yuan, Hua
%A Dong, Wenzong
%A Zhang, Shupeng
%A Liu, Shaofeng
%A Wei, Nan
%A Lu, Xingjie
%A Wei, Zhongwang
%A Ying, Hu
%A Dai, Yongjiu
%D 2023
%T Reprocessed MODIS Version 6.1 Leaf Area Index dataset
%U https://data.4tu.nl/articles/dataset/Reprocessed_MODIS_Version_6_1_Leaf_Area_Index_dataset/21858717
%R 10.4121/21858717.v2
%K Leaf Area Index (LAI)
%K Land Surface Modeling
%K Climate Modeling
%K temporal distribution
%X <h3>Introduction</h3><p>The leaf area index (LAI) data sets were generated by reprocessing the MODIS version 6.1 LAI products.</p><p>The raw data used include the MODIS LAI Version 6.1 products&nbsp;<a href="https://lpdaac.usgs.gov/products/mcd15a2hv061/" target="_blank">MCD15A2H</a>&nbsp;(2002.7.4-2021),&nbsp;<a href="https://lpdaac.usgs.gov/products/mod15a2hv061/" target="_blank">MOD15A2H</a>&nbsp;(2000.2.18-2002.6.26) (<a href="https://lpdaac.usgs.gov/products/mod15a2hv061/" target="_blank">Myneni et al., 2021</a>) and MODIS Land Cover Type product&nbsp;<a href="https://lpdaac.usgs.gov/products/mcd12q1v061/" target="_blank">MCD12Q1</a>&nbsp;(2001-2021) (<a href="https://lpdaac.usgs.gov/products/mcd12q1v061/" target="_blank">Friedl and Sulla-Menashe, 2022</a>).</p><p>The algorithm is mainly based on the two-step integrated method developed by <a href="https://doi.org/10.1016/j.rse.2011.01.001" target="_blank">Yuan et al. (2011)</a>, and the method of background value calculation was updated.</p><ul><li>For each year being reprocessed, the nearest 9-year data include itself are used.</li><li>We use the corresponding year's land cover data for calculating the multi-year average, local per class mean, per class mean and multi-year per class mean (ref. Fig. 4, Yuan et al., 2011).</li></ul><h3>Data description</h3><p>These monthly LAI data were provided at 0.5-degree resolution covering the period 2000-2021. Data of each year is stored in one NetCDF file, namely lai_monthly_0.5_{YEAR}.nc.</p><p>For LAI data with more spatial or temporal resolutions, see <a href="http://globalchange.bnu.edu.cn/research/laiv061" target="_blank">Land-Atmosphere Interaction Research Group at Sun Yat-sen University (bnu.edu.cn)</a>.</p><h4>Caution</h4><p>The reprocessed data for downloading consists two MODIS version 6.1 products, i.e., MCD15A2H (2002.7.4-2021) and MOD15A2H (2000.2.18-2002.6.26). The prefix “MCD” stands for a combined product, whose algorithm chooses the best pixel available from all the acquisitions of both MODIS sensors located on NASA’s Terra and Aqua satellites, while “MOD” data are retrieved only from the Terra satellite. We have found that their temporal-mean values were different especially in the equatorial region, which may result in an unrealistic trend (see Lin et al., 2022 for detailed discussion). Therefore, attention should be paid when using the reprocessed products for long-term trend analysis and data starting from year 2003 (i.e., only MCD) was recommended for LAI trend study.&nbsp;</p><h3><strong>Data citation</strong></h3><ol><li>Lin, W.; Yuan, H.; Dong, W.; Zhang, S.; Liu, S.; Wei, N.; Lu, X.; Wei, Z.; Hu, Y.; Dai, Y. Reprocessed MODIS Version 6.1 Leaf Area Index Dataset and Its Evaluation for Land Surface and Climate Modeling.&nbsp;<em>Remote Sens.</em>&nbsp;<strong>2023</strong>,&nbsp;<em>15</em>, 1780. https://doi.org/10.3390/rs15071780</li><li>Yuan, H., Dai, Y., Xiao, Z., Ji, D., Shangguan, W., 2011. Reprocessing the MODIS Leaf Area Index Products for Land Surface and Climate Modelling. Remote Sensing of Environment, 115(5), 1171-1187. doi:<a href="http://dx.doi.org/10.1016/j.rse.2011.01.001" target="_blank">10.1016/j.rse.2011.01.001</a></li></ol>
%I 4TU.ResearchData