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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Claim

Soil moisture in %(m3/m3) at 4 layer at 1000 m resolution in Qinghai-Tibet Plateau (QTP_DNN_Sm_L4)

Research datakeyboard_double_arrow_right Dataset 05 Mar 2023Publisher:Zenodo
Authors: Dong, Zhaoyu; Weng, Baisha; Yuheng Yang; Denghua Yan; Zhigang Ou; Wang, Hao;

doi: 10.5281/zenodo.7699592 , 10.5281/zenodo.7699591

Soil moisture in %(m3/m3) at 4 layer at 1000 m resolution in Qinghai-Tibet Plateau (QTP_DNN_Sm_L4)

Abstract

Based on the deep neural network, using the SMAP and ERA5 datasets as the target data, and considering the elements of the water cycle process and environmental factors as predictor variables for training, a daily multi-layer soil moisture dataset with a resolution of 1000 meters from 2001 to 2020 was produced. The data set is stored as integer data, scale=100000. File naming convention: 2001..2020 = time reference: period 2001-2020, QTP_DNN_Sm = Dataset ID, L1..L4 = 4 layer soil depth (0-7cm, 7-28cm, 28-100cm, 100-289cm), day1..day365/day366 = Date order within the year (January 1st - December 31st), pkl = Data storage format.

Keywords

Qinghai-Tibet Plateau, soil moisture

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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