Series or Parallel? An Exploration in Coupling Physical Model and Machine Learning Method for Disaggregating Satellite Microwave Soil Moisture
Author:
Affiliation:
1. College of Geoscience and Surveying Engineering, China University of Mining and Technology-Beijing, Beijing, China
2. Faculty of Geographical Science, Beijing Normal University, Beijing, China
Funder
Beijing Municipal Natural Science Foundation
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09926145.pdf?arnumber=9926145
Reference43 articles.
1. A survey on ensemble learning
2. Research on Ensemble Learning
3. A Soil Moisture Spatial and Temporal Resolution Improving Algorithm Based on Multi-Source Remote Sensing Data and GRNN Model
4. Machine Learning Techniques for Downscaling SMOS Satellite Soil Moisture Using MODIS Land Surface Temperature for Hydrological Application
5. Downscaling of passive microwave soil moisture retrievals based on spectral analysis
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