Soil moisture retrieval at high spatial resolution over alpine ecosystems on Nagqu-Tibetan plateau: A comparative study on semiempirical and machine learning approaches-Reference-Cited by-同舟云学术

Soil moisture retrieval at high spatial resolution over alpine ecosystems on Nagqu-Tibetan plateau: A comparative study on semiempirical and machine learning approaches

Published:2024-06 Issue: Volume:9 Page:100135
ISSN:2666-0172
Container-title:Science of Remote Sensing
language:en
Short-container-title:Science of Remote Sensing

Author:

Taghavi-Bayat Aida^ORCID,Gerke Markus^ORCID,Riedel Björn^ORCID

Funder

Deutsche Forschungsgemeinschaft

Publisher

Elsevier BV

Reference63 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 Sensing of Environment,2021

2. Biomass Assessment of agricultural crops using multi-temporal dual-polarimetric TerraSAR-X data;Ahmadian;PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science,2019

3. Decomposition-based soil moisture estimation using UAVSAR fully polarimetric images;Akhavan;Agronomy,2021

4. Retrieving surface soil moisture at high spatio-temporal resolution from a synergy between Sentinel-1 radar and Landsat thermal data: a study case over bare soil;Amazirh;Remote Sensing of Environment,2018

5. Spatiotemporal data partitioning for distributed random forest algorithm: air quality prediction using imbalanced big spatiotemporal data on spark distributed framework;Asgari;Environmental Technology & Innovation,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dual-polarization vegetation indices for the Sentinel-1 sar sensor and its correlation to forest biomass from Atlantic Forest fragments;CERNE;2024