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Zhu, Liujun, Walker, Jeffrey P., Tsang, Leung, Huang, Huanting, Ye, Nan, Rüdiger, Christoph (2019) A multi-frequency framework for soil moisture retrieval from time series radar data. Remote Sensing of Environment, 235. 111433pp. doi:10.1016/j.rse.2019.111433

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Reference TypeJournal (article/letter/editorial)
TitleA multi-frequency framework for soil moisture retrieval from time series radar data
JournalRemote Sensing of Environment
AuthorsZhu, LiujunAuthor
Walker, Jeffrey P.Author
Tsang, LeungAuthor
Huang, HuantingAuthor
Ye, NanAuthor
Rüdiger, ChristophAuthor
Year2019 (December)Volume235
PublisherElsevier BV
DOIdoi:10.1016/j.rse.2019.111433Search in ResearchGate
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Mindat Ref. ID9443352Long-form Identifiermindat:1:5:9443352:0
GUID0
Full ReferenceZhu, Liujun, Walker, Jeffrey P., Tsang, Leung, Huang, Huanting, Ye, Nan, Rüdiger, Christoph (2019) A multi-frequency framework for soil moisture retrieval from time series radar data. Remote Sensing of Environment, 235. 111433pp. doi:10.1016/j.rse.2019.111433
Plain TextZhu, Liujun, Walker, Jeffrey P., Tsang, Leung, Huang, Huanting, Ye, Nan, Rüdiger, Christoph (2019) A multi-frequency framework for soil moisture retrieval from time series radar data. Remote Sensing of Environment, 235. 111433pp. doi:10.1016/j.rse.2019.111433
In(n.d.) Remote Sensing of Environment Vol. 235. Elsevier BV

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Zhu, Liujun, Walker, Jeffrey P., Tsang, Leung, Huang, Huanting, Ye, Nan, Rüdiger, Christoph (2019) Soil moisture retrieval from time series multi-angular radar data using a dry down constraint. Remote Sensing of Environment, 231. 111237pp. doi:10.1016/j.rse.2019.111237
Zhu, Liujun, Walker, Jeffrey P., Ye, Nan, Rüdiger, Christoph (2019) Roughness and vegetation change detection: A pre-processing for soil moisture retrieval from multi-temporal SAR imagery. Remote Sensing of Environment, 225. 93-106 doi:10.1016/j.rse.2019.02.027
Zhu, Liujun, Yuan, Shanshui, Liu, Yi, Chen, Cheng, Walker, Jeffrey P. (2023) Time series soil moisture retrieval from SAR data: Multi-temporal constraints and a global validation. Remote Sensing of Environment, 287. 113466 doi:10.1016/j.rse.2023.113466
Zhu, Liujun, Walker, Jeffrey P., Shen, Xiaoji (2020) Stochastic ensemble methods for multi-SAR-mission soil moisture retrieval. Remote Sensing of Environment, 251. 112099pp. doi:10.1016/j.rse.2020.112099
Zhu, Liujun, Si, Rui, Shen, Xiaoji, Walker, Jeffrey P. (2022) An advanced change detection method for time-series soil moisture retrieval from Sentinel-1. Remote Sensing of Environment, 279. 113137 doi:10.1016/j.rse.2022.113137
Zhu, Liujun, Dai, Junjie, Liu, Yi, Yuan, Shanshui, Qin, Tianling, Walker, Jeffrey P. (2024) A cross-resolution transfer learning approach for soil moisture retrieval from Sentinel-1 using limited training samples. Remote Sensing of Environment, 301. 113944 doi:10.1016/j.rse.2023.113944
Shen, Xiaoji, Fan, Lei, Zuo, Tengteng, Cui, Tianyu, Wu, Jiayi, Ye, Nan, Brakhasi, Foad, Wu, Xiaoling, Zhu, Liujun, Wigneron, Jean-Pierre, Walker, Jeffrey P., Zhang, Ke (2024) P-band radiometry for enhanced vegetation optical depth (VOD) and soil moisture retrieval in dense crop canopies. Remote Sensing of Environment, 313. doi:10.1016/j.rse.2024.114353
Peischl, Sandy, Walker, Jeffrey P., Ye, Nan, Ryu, Dongryeol, Kerr, Yann (2014) Sensitivity of multi-parameter soil moisture retrievals to incidence angle configuration. Remote Sensing of Environment, 143. 64-72 doi:10.1016/j.rse.2013.11.019
Zhu, Liujun, Cai, Qi, Jin, Junliang, Yuan, Shanshui, Shen, Xiaoji, Walker, Jeffrey P. (2025) Multi-Scale domain adaptation for high-resolution soil moisture retrieval from synthetic aperture radar in data-scarce regions. Journal of Hydrology, 657. doi:10.1016/j.jhydrol.2025.133073
Ye, N., Walker, J.P., Rüdiger, C., Ryu, D., Gurney, R.J. (2018) Surface rock effects on soil moisture retrieval from L-band passive microwave observations. Remote Sensing of Environment, 215. 33-43 doi:10.1016/j.rse.2018.05.025
Shen, Xiaoji, Walker, Jeffrey P., Ye, Nan, Wu, Xiaoling, Boopathi, Nithyapriya, Yeo, In-Young, Zhang, Linlin, Zhu, Liujun (2021) Soil Moisture Retrieval Depth of P- and L-Band Radiometry: Predictions and Observations. IEEE Transactions on Geoscience and Remote Sensing, 59 (8) 6814-6822 doi:10.1109/tgrs.2020.3026384
 
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