1-km soil moisture retrieval using multi-temporal dual-channel SAR data from Sentinel-1 A/B satellites in a semi-arid watershed-Reference-Cited by-同舟云学术

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1-km soil moisture retrieval using multi-temporal dual-channel SAR data from Sentinel-1 A/B satellites in a semi-arid watershed

Published:2023-01 Issue: Volume:284 Page:113334
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Wang Zhen,Zhao Tianjie,Shi Jiancheng,Wang Hongquan,Ji Dabin,Yao Panpan,Zheng Jingyao,Zhao Xuesheng,Xu Xia

Funder

Chinese Academy of Sciences

National Key Research and Development Program of China

European Space Agency

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference99 articles.

1. Assessment of the operational applicability of RADARSAT-1 data for surface soil moisture estimation;Alvarez-Mozos;IEEE Trans.Geosci.Remote Sens.,2006

2. Four-component decomposition of polarimetric SAR images with deorientation;An;IEEE Geosci. Remote Sens. Lett.,2011

3. Vegetation modeled as a water cloud;Attema;Radio Sci.,1978

4. Detection of frozen soil using Sentinel-1 SAR data;Baghdadi;Remote Sens.,2018

5. Calibration of the water cloud model at C-band for winter crop fields and grasslands;Baghdadi;Remote Sens.,2017

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1. Continuous Ground Moisture Monitoring at Limestone Quarry Using Multi-Sensor SAR Images and in Situ IoT Sensors;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Comparative Analysis of Two Angle Normalization Approaches for SAR Backscatter: Simulation and Satellite Observation-Based Evaluation in Soil Moisture Retrieval;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

3. Comparison of three machine learning algorithms for retrieving soil moisture information from Sentinel-1A SAR data in northwest Shandong plain, China;Advances in Space Research;2024-07

4. Inversion of soil moisture based on improved change detection method using Sentinel-1A and MODIS time-series data;International Conference on Remote Sensing, Surveying, and Mapping (RSSM 2024);2024-06-03

5. Inversion of large-scale citrus soil moisture using multi-temporal Sentinel-1 and Landsat-8 data;Agricultural Water Management;2024-04

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