A deep neural network based SMAP soil moisture product-Reference-Cited by-同舟云学术

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A deep neural network based SMAP soil moisture product

Published:2022-08 Issue: Volume:277 Page:113059
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Gao Lun,Gao Qiang,Zhang Hankui,Li Xiaojun,Chaubell Mario Julian,Ebtehaj Ardeshir,Shen Lian,Wigneron Jean-Pierre

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference131 articles.

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2. Partitioning of historical precipitation into evaporation and runoff based on hydrologic dynamics identified with recent smap satellite measurements;Akbar;Water Resour. Res.,2020

3. A bare ground evaporation revision in the ecmwf land-surface scheme: evaluation of its impact using ground soil moisture and satellite microwave data;Albergel;Hydrol. Earth Syst. Sci.,2012

4. Evaluating soil moisture retrievals from esa’s smos and nasa’s smap brightness temperature datasets;Al-Yaari;Remote Sens. Environ.,2017

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

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