A5100321490- Soil Moisture and Remote Sensing
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Precipitation Measurement and Analysis
- Neural Networks and Applications
- Electromagnetic Simulation and Numerical Methods
- Underwater Acoustics Research
- Microwave Engineering and Waveguides
- Computational Physics and Python Applications
- Cryospheric studies and observations
- Landslides and related hazards
- Climate change and permafrost
- Soil Geostatistics and Mapping
North China Institute of Science and Technology
2023
China Institute of Water Resources and Hydropower Research
2022
Hunan University of Science and Technology
2012
Carleton University
1998-1999
Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation, optimization. After learning abstracting from data, through a process called training, neural network models are used during design provide instant answers the task learned. Appropriate structure suitable training algorithm two of major issues in developing for applications. Together, they decide amount data required, accuracy that could possibly be achieved, more importantly...
Neural networks recently gained attention as a fast and flexible vehicle for microwave modeling, simulation, optimization. This paper addresses new task in this area, namely, the development of libraries neural models passive active components, task, with potential significance to many simulators. However, developing is very costly due massive data generation repeated network training. A hierarchical approach presented paper, allowing both functional knowledge library inherent structural be...
Abstract. Land surface soil moisture (SM) plays a critical role in hydrological processes and terrestrial ecosystems desertification areas. Passive microwave remote-sensing products such as the Soil Moisture Active (SMAP) satellite have been shown to monitor water well. However, coarse spatial resolution lack of full coverage these greatly limit their application areas undergoing desertification. In order overcome limitations, combination multiple machine learning methods, including linear...
In this article, we present the first demonstration of FengYun-3E (FY3E) Global Navigation Satellite System Occultation Sounder II-Reflectometry (GNOS-R) payload's capacity to detect near-surface soil freeze/thaw (F/T) states. This study offers an initial analysis F/T retrieval algorithm applied data collected from Arctic Circle, underscoring GNOS-R's potential deliver long-term products. Data for period extending launch day GNOS-R (Day Year (DOY) 179, 2021) DOY 270 in 2022 were analyzed...
Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation, optimization. After learning abstracting from data, through a process called training, neural network models are used during design provide instant answers the task learned. Appropriate structure suitable training algorithm two of major issues in developing for applications. Together, they decide amount data required, accuracy that could possibly be achieved, more importantly...
The Land Surface GNSS Reflection Simulator (LAGRS)-Soil model represents a significant advancement in soil moisture detection with the aid of Global Navigation Satellite System (GNSS) Occultation Sounder-Reflectometry (GNOS-R) technology, which is one payload Fengyun-3E (FY-3E) satellite that was launched on 5 July 2021. To fully exploit properties noncoherent scattering, LAGRS-Soil has capability to calculate DDM information for different observational geometries, relies random surface...
A coherent vegetation backscattering model which was developed by modifying the Michigan grassland mode for application of agricultural fields with uniform distribution used in this research. The coherence effect between various scattering mechanisms is considered model. An experiment carried out over a flat agriculture area located at Gongzhuling, Jilin province China. Five rice and four corn were selected as test targets plant soil parameters collected growing season models inputs. to...