Other Data Paper Zone I Versions ZH2
MuSyQ GF-series 16m/10days fractional vegetation cover product (from 2018 to 2020 across China version 01)
Dataset URL >>
: 2021 - 06 - 21
: 2021 - 08 - 19
: 2021 - 08 - 19
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Abstract & Keywords
Abstract: Fractional vegetation cover (FVC) is one of the important indicators to monitor the vegetation conditions on earth. Remote sensing is a main way to obtain the dynamic FVC at large scale. However, there is no standard high-resolution FVC product worldwide. Taking advantage of the high spatial and temporal resolution of Gaofen-1, MuSyQ GF-series FVC product with 16m/10days resolution in China from 2018 to 2020 (version 01) was produced using the gap probability theory for forest type and the dimidiate pixel model based on normalized difference vegetation index (NDVI) for other vegetation types. This product can provide reliable data for vegetation monitoring in China.
Keywords: Fractional vegetation cover (FVC); gap probability theory; dimidiate pixel model; China; Gaofen-1 (GF-1)
Dataset Profile
TitleMuSyQ GF-series 16 m/10 days fractional vegetation cover product (from 2018 to 2020 across China version 01)
Data corresponding authorLI Jing (lijing01@radi.ac.cn); LIU Qinhuo (liuqh@radi.ac.cn)
Data authorsZHAO Jing, LI Jing, ZHANG Zhaoxing, WU Shanlong, ZHONG Bo, LIU Qinhuo
Time range2018–2020
Geographical scopeChina
Spatial resolution16 m
Time resolution10 days
Data volume3.72 TB
Data format*.h5
Data service system<http://www.doi.org/10.11922/sciencedb.j00001.00266>
Sources of fundingNational Key Research and Development Program (2018YFA0605503), GF Project (21-Y20B02-9003-19/22).
Dataset compositionThe product consists of 2 subsets in total. Subset 1 is made up of the fractional vegetation cover image, and Subset 2 is made up of the quality control information of each pixel.
Article and author information
Zhao Jing
Jing Li
Zhaoxing Zhang
Wu Shanlong
Bo Zhong
Qinhuo Liu
Publication records
Released: Aug. 19, 2021 ( VersionsZH2