An Efficient Technique for Rapid Estimation of Flood Water Levels: Combining CYGNSS GNSS-R L1 Data with DTMS
Author:
Affiliation:
1. Chang’an University,College of Geological Engineering and Geomatics,Xi’an,China,710054
2. Universitat Politècnica de Catalunya – BarcelonaTech,CommSensLab – UPC,Barcelona,Spain
Funder
National Natural Science Foundation of China
Research and Development
State Key Laboratory of Geo-Information Engineering
Fundamental Research Funds for the Central Universities
China Scholarship Council
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641722.pdf?arnumber=10641722
Reference22 articles.
1. Analysis of coastal wind speed retrieval from CYGNSS mission using artificial neural network
2. Significant Wave Height Retrieval Based on Multivariable Regression Models Developed With CYGNSS Data
3. Sensitivity of GNSS-R Spaceborne Observations to Soil Moisture and Vegetation
4. Above-Ground Biomass Retrieval over Tropical Forests: A Novel GNSS-R Approach with CyGNSS
5. CYGNSS data map flood inundation during the 2017 Atlantic hurricane season
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