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Data Details

China’s Terrestrial UNVI Multidimensional Dataset (2018-2021)


ZHAO Hengqian1LIU Xuanqi1ZHANG Lifu*2CHEN Jiahua2FU Hancong1MA Ke1
1 College of Geoscience and Surveying Engineering，China university of mining and technology (Beijing)，Beijing 100083，China2 Aerospace Information Research Institute，Institute of Remote Sensing and Digital Earth，Chinese Academy of Sciences，Beijing 100101，China

DOI:10.3974/geodb.2022.12.01.V1

Published:Dec. 2022

Visitors：2690       Data Files Downloaded：318      
Data Downloaded：1018828.85 MB      Citations：

Key Words：

UNVI,MODIS,Vegetation Index,BRDF-C,Long Time Series

Abstract：

Vegetation index data products are widely used in the inversion of physical and chemical parameters of vegetation, land cover classification and changes studies. Traditional vegetation index products, such as AVHRR-NDVI, are sensitive to soil background changes and have the problem of high value saturation, which is easy to cause the decrease of sensitivity to vegetation detection. The China’s Terrestrial UNVI Multidimensional Dataset (2018-2021) was developed based on the MODIS surface reflectance product MOD09GA, using the Universal Pattern Decomposition algorithm UPDM (Universal Pattern Decomposition Method), which takes 16 days as the synthesis cycle. The practices show that the UNVI has more advantages in reflecting the change of vegetation cover and quantitative inversion of vegetation physical and chemical parameters compared with traditional NDVI products. The synthesis algorithm takes the number of days without cloud data in the synthesis period N as the judgment condition, and uses the Angle normalized synthesis method, the maximum synthesis method in a limited perspective, the direct calculation method and the maximum synthesis method MVC as the main synthesis algorithm to calculate the UNVI. Thus, the 2018-2021 China terrestrial UNVI products with a time resolution of 16 d and a spatial resolution of about 463 m was synthesized. The dataset includes the UNVI products of China terrestrial vegetation indices in 23 time periods with 16 d intervals from 2018 to 2021. The UNVI dataset is archived in .mdd format, and consists of 8 data files with data size of 43.5 GB (Compressed to 4 files with 12.5 GB). The tool and program for .mdd data format can be accessed by the references [23] and [24].Browse

Foundation Item：

Ministry of Education of P. R. China (2022JCCXDC01); China University of Mining and Technology (Beijing) (2020QN07)

Data Citation：

ZHAO Hengqian, LIU Xuanqi, ZHANG Lifu*, CHEN Jiahua, FU Hancong, MA Ke.China’s Terrestrial UNVI Multidimensional Dataset (2018-2021)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.12.01.V1.

ZHAO Hengqian, LIU Xuanqi, ZHANG Lifu, et al. China’s terrestrial UNVI multidimensional dataset (2018-2021) [J]. Journal of Global Change Data & Discovery, 2022, 6(4): 645–655

References：

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     [23] Zhang, L. F., Sun, X. J., Zhang, X., et al. New version for the multi-dimensional data format (MDD) analysis tool (MARS v2.03) [J/DB/OL]. Digital Journal of Global Change Data Repository, 2017. https://doi.org/10.3974/geodb.2017.02.20.V1.
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Data Product:

ID Data Name Data Size Operation
0Datapaper_UNVI_China_2018-2021.pdf5747.00kbDownLoad
1 2018_UNVI.zip 3048892.23KB
2 2019_UNVI.zip 3376913.76KB
3 2020_UNVI.zip 3374122.70KB
4 2021_UNVI.zip 3378042.84KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum