Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning-Reference-Cited by-同舟云学术

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Improved soil moisture estimation: Synergistic use of satellite observations and land surface models over CONUS based on machine learning

Published:2022-06 Issue: Volume:609 Page:127749
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Lee Jaese,Park Sumin,Im Jungho,Yoo Cheolhee,Seo Eunkyo

Funder

National Research Foundation of Korea

Korea Ministry of Science and ICT

Korea Meteorological Administration

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference127 articles.

1. Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements;Al-Yaari;Remote Sens. Environ.,2019

2. Downscaling SMAP radiometer soil moisture over the CONUS using an ensemble learning method;Abbaszadeh;Water Resour. Res.,2019

3. Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: 2. Global statistical relationships;Aires;J. Geophys. Res. D Atmos.,2005

4. From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations;Albergel;Hydrol. Earth Syst. Sci.,2008

5. A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the integrated forecast system;Balsamo;J. Hydrometeorol.,2009

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5. ASCAT2SMAP: Image-to-Image Translation to Obtain L-Band-Like Soil Moisture From C-Band Satellite Data;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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