A novel land surface temperature reconstruction method and its application for downscaling surface soil moisture with machine learning-Reference-Cited by-同舟云学术

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A novel land surface temperature reconstruction method and its application for downscaling surface soil moisture with machine learning

Published:2024-05 Issue: Volume:634 Page:131051
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Güngör Şahin Onur,Gündüz Orhan^ORCID

Funder

TÜBİTAK

Publisher

Elsevier BV

Reference70 articles.

1. Generating surface soil moisture at 30 m spatial resolution using both data fusion and machine learning toward better water resources management at the field scale;Abowarda;Remote Sens. Environ.,2021

2. Hydrological storage length scales represented by remote sensing estimates of soil moisture and precipitation;Akbar;Water Resour. Res.,2018

3. Performance evaluation of satellite- and model-based precipitation products over varying climate and complex topography;Amjad;J. Hydrol.,2020

4. Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling;Beck;Hydrol. Earth Syst. Sci.,2017

5. Daily evaluation of 26 precipitation datasets using stage-IV gauge-radar data for the CONUS;Beck;Hydrol. Earth Syst. Sci.,2019

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