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GLCC: global leaf chlorophyll content dataset over 2003–2012 and 2018–2020 derived from MERIS/OLCI satellite data

posted on 09.08.2022, 17:03 authored by Xiaojin QianXiaojin Qian, Liangyun LiuLiangyun Liu, Xidong Chen, Xiao Zhang, Siyuan Chen, Qi Sun

Leaf chlorophyll content (LCC) is an important plant physiological trait and a proxy for leaf photosynthetic capacity. This dataset (GLCC) contains global 7-day LCC data with 500 m resolution for the period 2003–2012 to 2018–2020, produced from ENVISAT MERIS and Sentinel-3 OLCI satellite data using a physically-based radiative transfer modeling approach. This new LCC dataset spanning nearly 20 years will provide a valuable opportunity for the monitoring of vegetation growth and terrestrial carbon cycle modeling.

Each .rar file contains 52 folders named “YYYYMMDD”, except for the years 2012, 2018 and 2020. The "2012_LCC", "2018_LCC" and "2020_LCC" .rar files contain only 13, 12 and 24 folders respectively. Each “YYYYMMDD” folder contains LCC data stored in GeoTIFF format, named “ESACCI-LC-L3-SR-MERIS-500m-P7D-h**v**-YYYYMMDD-v2.0-MODISTile-LCC.tif” and “S3_YYYYMMDD_h**v**_7DaySR-MODISTile-LCC.tif” for MERIS LCC dataset and OLCI LCC dataset, respectively, where “h**v**” is referenced to the MODIS tile. The scale factor of the data is 0.01.


Quantitative remote sensing of vegetation

National Natural Science Foundation of China

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Innovative Research Program of the International Research Center of Big Data for Sustainable Development Goals (Grant No. CBAS2022IRP01)

Open Fund of State Key Laboratory of Remote Sensing Science (Grant No. OFSLRSS202216)

Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications (Grant No. NY221145)


Research Institution(s)

School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210023, China

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