Dataset List

Vol.|Area

No.11 Vol.11,2024
No.10 Vol.11,2024
No.09 Vol.11,2024
No.08 Vol.11,2024
No.07 Vol.11,2024
No.06 Vol.11,2024
No.05 Vol.11,2024
No.04 Vol.11,2024
No.03 Vol.11,2024
No.02 Vol.11,2024
No.01 Vol.11,2024
No.12 Vol.10,2023
No.11 Vol.10,2023
No.10 Vol.10,2023
No.09 Vol.10,2023
No.08 Vol.10,2023
No.07 Vol.10,2023
No.06 Vol.10,2023
No.05 Vol.10,2023
No.04 Vol.10,2023
No.03 Vol.10,2023
No.02 Vol.10,2023
No.01 Vol.10,2023
No.12 Vol.9,2022
No.11 Vol.9,2022
No.10 Vol.9,2022
No.09 Vol.9,2022
No.08 Vol.9,2022
No.07 Vol.9,2022
No.06 Vol.9,2022
No.05 Vol.9,2022
No.04 Vol.9,2022
No.03 Vol.9,2022
No.02 Vol.9,2022
No.01 Vol.9,2022
No.12 Vol.8,2021
No.11 Vol.8,2021
No.10 Vol.8,2021
No.09 Vol.8,2021
No.08 Vol.8,2021
No.07 Vol.8,2021
No.06 Vol.8,2021
No.05 Vol.8,2021
No.04 Vol.8,2021
No.03 Vol.8,2021
No.03 Vol.8,2021
No.02 Vol.8,2021
No.01 Vol.8,2021
No.09 Vol.7,2020
No.08 Vol.7,2020
No.07 Vol.7,2020
No.06 Vol.7,2020
No.05 Vol.7,2020
No.04 Vol.7,2020
No.03 Vol.7,2020
No.02 Vol.7,2020
No.01 Vol.7,2020
No.06 Vol.6,2019
No.05 Vol.6,2019
No.04 Vol.6,2019
No.03 Vol.6,2019
No.02 Vol.6,2019
No.01 Vol.6,2019
No.08 Vol.5,2018
No.07 Vol.5,2018
No.06 Vol.5,2018
No.05 Vol.5,2018
No.04 Vol.5,2018
No.03 Vol.5,2018
No.02 Vol.5,2018
No.01 Vol.5,2018
No.04 Vol.4,2017
No.03 Vol.4,2017
No.02 Vol.4,2017
No.01 Vol.4,2017
No.09 Vol.3,2016
No.08 Vol.3,2016
No.07 Vol.3,2016
No.06 Vol.3,2016
No.05 Vol.3,2016
No.04 Vol.3,2016
No.03 Vol.3,2016
No.02 Vol.3,2016
No.01 Vol.3,2016
No.02 Vol.2,2015
No.01 Vol.2,2015
No.02 Vol.1,2014
No.01 Vol.1,2014
China
Asia
Oceanic region
African
European
North American
South American
Arctic
Global Scale
Data Details

Reprocessing Dataset of Global Soil Moisture Product (2015-2019)


LIU Yangxiaoyue1,2
1 Guangzhou Institute of Geography，Guangdong Academy of Sciences，Guangzhou 510070，China2 Southern Marine Science and Engineering Guangdong Laboratory，Guangzhou 511458，China

DOI:10.3974/geodb.2020.08.03.V1

Published:Nov. 2020

Visitors：11640       Data Files Downloaded：995      
Data Downloaded：184937.02 MB      Citations：

Key Words：

data reprocessing,soil moisture,global,daily,ECV SM,IEEE Access

Abstract：

Reprocessing dataset of global soil moisture product (2015-2019) was developed based on integrating the Essential Climate Variable(ECV) soil moisture (SM) multi-source satellite fusion products(1d，0.25°x0.25°) and the Soil Moisture Active Passive (SMAP) soil moisture products through re-projection, re-sampling and weighted calculation. The dataset was validated by 134 monitoring stations in 8 soil moisture monitoring networks in Europe, the results show that the spatial integrity of soil moisture products is significantly improved (about 20%), and the data quality is also improved compared with the original ECV SM. The dataset is archived in .tif data format in 1737 data files with the data size of 6.71 GB (compressed into five data files with 931 MB). The analysis and finding results based on this dataset have been published in IEEE Access, Vol. 8, 2020.Browse

Foundation Item：

Ministry of Human Resources and Social Security of P. R. China, National Post-Doctor Regulatory Commission (BX20200100); National Earth Observation Data Center (NODAOP2020002); Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou, GML2019ZD0301)

Data Citation：

LIU Yangxiaoyue. Reprocessing Dataset of Global Soil Moisture Product (2015-2019)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2020. https://doi.org/10.3974/geodb.2020.08.03.V1.

WANG Zhuoying, LIU Yangxiaoyue. Global soil moisture retrievals fusion dataset (2015-2019) [J]. Journal of Global Change Data & Discovery, 2020, 4(4): 315-324. https://doi.org/10.3974/geodp.2020.04.01.

Data Product:

ID Data Name Data Size Operation
0Datapaper_Soilmoisture_2015-2019.pdf2345.00kbDownLoad
1 SM_2015_0331_1231.rar 162841.29KB
2 SM_2016_0101_1231.rar 198774.92KB
3 SM_2017_0101_1231.rar 198419.00KB
4 SM_2018_0101_1231.rar 198014.72KB
5 SM_2019_0101_1231.rar 196160.30KB
Co-Sponsors
Superintend