58 citations as recorded by crossref.

1. Low‐Rank Gap Filling and Downscaling for SMAP Soil Moisture Datasets K. Beale et al.
2. Multivariate remotely sensed and in-situ data assimilation for enhancing community WRF-Hydro model forecasting P. Abbaszadeh et al.
3. Mechanism-learning coupling paradigms for parameter inversion and simulation in earth surface systems H. Shen & L. Zhang
4. Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China A. Nadeem et al.
5. Deep learning in environmental remote sensing: Achievements and challenges Q. Yuan et al.
6. Surface soil moisture retrieval based on transfer learning using SAR data on a local scale E. Hemmati & M. Sahebi
7. Spatial Downscaling of Satellite-Based Soil Moisture Products Using Machine Learning Techniques: A Review I. Senanayake et al.
8. A review of forward modelling and retrieval approaches for forest soil moisture and vegetation optical depth using L-band radiometry A. Colliander et al.
9. Improving SMAP freeze-thaw retrievals for pavements using effective soil temperature from GEOS-5: Evaluation against in situ road temperature data over the U.S S. Kraatz et al.
10. An Integrated Learning Framework for Seamless High-Resolution Soil Moisture Estimation Y. Jing et al.
11. Cosmic-Ray neutron Sensor PYthon tool (crspy 1.2.1): an open-source tool for the processing of cosmic-ray neutron and soil moisture data D. Power et al.
12. A Multiscale Deep Learning Model for Soil Moisture Integrating Satellite and In Situ Data J. Liu et al.
13. Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data C. Lorenz et al.
14. Soil-Permittivity Estimation Under Grassland Using Machine-Learning and Polarimetric Decomposition Techniques R. Hansch et al.
15. Estimating and Downscaling ESA-CCI Soil Moisture Using Multi-Source Remote Sensing Images and Stacking-Based Ensemble Learning Algorithms in the Shandian River Basin, China L. Wang & Y. Gao
16. Downscaling of soil moisture in satellite-borne GNSS-R based on multi-model fusion Y. Liang et al.
17. How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture? L. Zappa et al.
18. Soil moisture downscaling in the state of Oklahoma: Employing advanced machine learning S. Koujani et al.
19. A Bayesian Deep Image Prior Downscaling Approach for High-Resolution Soil Moisture Estimation Y. Fang et al.
20. Improved downscaling of microwave-based surface soil moisture over a typical subtropical monsoon region L. Li et al.
21. Estimating catchment scale soil moisture at a high spatial resolution: Integrating remote sensing and machine learning I. Senanayake et al.
22. The International Soil Moisture Network: serving Earth system science for over a decade W. Dorigo et al.
23. An Intercomparison Study of Algorithms for Downscaling SMAP Radiometer Soil Moisture Retrievals L. Fang et al.
24. Spatial Downscaling of Soil Moisture Product to Generate High-Resolution Data: A Multi-Source Approach over Heterogeneous Landscapes in Kenya A. Abebe et al.
25. An Approach for Downscaling SMAP Soil Moisture by Combining Sentinel-1 SAR and MODIS Data J. Bai et al.
26. Gap-free global annual soil moisture: 15 km grids for 1991–2018 M. Guevara et al.
27. Deriving Field Scale Soil Moisture from Satellite Observations and Ground Measurements in a Hilly Agricultural Region L. Zappa et al.
28. Near‐real‐time one‐kilometre Soil Moisture Active Passive soil moisture data product J. Yin et al.
29. Mapping near-real-time soil moisture dynamics over Tasmania with transfer learning M. Widyastuti et al.
30. Using of Remote Sensing-Based Auxiliary Variables for Soil Moisture Scaling and Mapping Z. Zhao et al.
31. Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations C. Zheng et al.
32. An Operational Downscaling Method of Solar-Induced Chlorophyll Fluorescence (SIF) for Regional Drought Monitoring Z. Hong et al.
33. Sensitive Feature Evaluation for Soil Moisture Retrieval Based on Multi-Source Remote Sensing Data with Few In-Situ Measurements: A Case Study of the Continental U.S. L. Zhang et al.
34. A Semi-Physical Approach for Downscaling Satellite Soil Moisture Data in a Typical Cold Alpine Area, Northwest China Z. Cao et al.
35. Estimation and Assessment of the Root Zone Soil Moisture from Near-Surface Measurements over Huai River Basin E. Liu et al.
36. Downscaling CLDAS Soil Moisture Product by Integrating Sentinel-1 and Sentinel-2 Data over Agricultural Area H. Ma et al.
37. A Remote Sensing Driven Soil Moisture Estimator: Uncertain Downscaling With Geostatistically Based Use of Ancillary Data M. Karamouz et al.
38. A New Approach for Soil Moisture Downscaling in the Presence of Seasonal Difference R. Yan & J. Bai
39. An Overview of Machine-Learning Methods for Soil Moisture Estimation M. Taheri et al.
40. A 21-year dataset (2000–2020) of gap-free global daily surface soil moisture at 1-km grid resolution C. Zheng et al.
41. Estimating soil moisture at farm scale with high spatial resolution: integrating remote sensing data, and machine learning D. Wang et al.
42. Spatial Downscaling Methods of Soil Moisture Based on Multisource Remote Sensing Data and Its Application S. Chen et al.
43. Disaggregating satellite soil moisture products based on soil thermal inertia: A comparison of a downscaling model built at two spatial scales I. Senanayake et al.
44. Assessing the Potential of Combined SMAP and In-Situ Soil Moisture for Improving Streamflow Forecast S. Wakigari & R. Leconte
45. Assessing the influence of model inputs on performance of the EMT + VS soil moisture downscaling model for a large foothills region in Northern Colorado S. Fischer et al.
46. Space–time variability in soil moisture droughts in the Himalayan region S. Nepal et al.
47. A machine learning-based approach for generating high-resolution soil moisture from SMAP products Y. Zhang et al.
48. Development of the global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) Z. Zhang et al.
49. Improving SMAP soil moisture spatial resolution in different climatic conditions using remote sensing data F. Imanpour et al.
50. 地球表层特征参量反演与模拟的机理<bold>-</bold>学习耦合范式 焕. 沈 & 良. 张
51. A Spatial Downscaling Method for Remote Sensing Soil Moisture Using Adaptive Weighted Stacking Strategy M. Xing et al.
52. A Value-Consistent Method for Downscaling SMAP Passive Soil Moisture With MODIS Products Using Self-Adaptive Window F. Wen et al.
53. A Microwave–Optical Multi-Stage Synergistic Daily 30 m Soil Moisture Downscaling Framework H. Xie et al.
54. Daily High-Resolution Land Surface Freeze/Thaw Detection Using Sentinel-1 and AMSR2 Data J. Wang et al.
55. Enhancing Spatial Resolution of SMAP Soil Moisture Products through Spatial Downscaling over a Large Watershed: A Case Study for the Susquehanna River Basin in the Northeastern United States S. Wakigari & R. Leconte
56. Enhanced Surface Soil Moisture Retrieval at High Spatial Resolution From the Integration of Satellite Observations and Soil Pedotransfer Functions P. Leng et al.
57. Potential of Remote Sensing Images for Soil Moisture Retrieving Using Ensemble Learning Methods in Vegetation-Covered Area Y. Gao et al.
58. A Multi-Layer Perceptron Approach to Downscaling Geostationary Land Surface Temperature in Urban Areas A. Hurduc et al.