Next Article in Journal
UAV-Based Automatic Detection and Monitoring of Chestnut Trees
Previous Article in Journal
Intercomparisons of Long-Term Atmospheric Temperature and Humidity Profile Retrievals
Previous Article in Special Issue
SAR Backscatter and InSAR Coherence for Monitoring Wetland Extent, Flood Pulse and Vegetation: A Study of the Amazon Lowland
Article Menu
Issue 7 (April-1) cover image

Export Article

Open AccessLetter
Remote Sens. 2019, 11(7), 854; https://doi.org/10.3390/rs11070854

Using CYGNSS Data to Monitor China’s Flood Inundation during Typhoon and Extreme Precipitation Events in 2017

1
Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing 100871, China
2
Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
3
Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
4
School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73019, USA
*
Author to whom correspondence should be addressed.
Received: 20 February 2019 / Revised: 2 April 2019 / Accepted: 3 April 2019 / Published: 9 April 2019
(This article belongs to the Special Issue Remote Sensing Water Cycle: Theory, Sensors, Data, and Applications)
  |  
PDF [3308 KB, uploaded 9 April 2019]
  |  

Abstract

NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission, launched in 2016, is a small satellite constellation designed to measure the ocean surface wind speed in hurricanes and tropical cyclones. To explore its additional capabilities for applications on the land surface, this study investigated the advantages and limitations of using CYGNSS data to monitor flood inundation during typhoon and extreme precipitation events in southeast China in 2017. The results showed that despite the lack of quantitative evaluation, the CYGNSS-derived surface reflectivity (SR) and flood inundation area was qualitatively consistent with the Global Precipitation Measurement (GPM)-derived precipitation and Soil Moisture Active Passive (SMAP)/Soil Moisture and Ocean Salinity (SMOS)-derived total brightness temperature at circular polarization ( T b C ). The results provide supporting evidence for further designation of Global Navigation Satellite System (GNSS) reflectometry (GNSS-R) constellations to monitor land surface hydrology. View Full-Text
Keywords: CYGNSS; GNSS-R; flood inundation; typhoon; extreme precipitation CYGNSS; GNSS-R; flood inundation; typhoon; extreme precipitation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Wan, W.; Liu, B.; Zeng, Z.; Chen, X.; Wu, G.; Xu, L.; Chen, X.; Hong, Y. Using CYGNSS Data to Monitor China’s Flood Inundation during Typhoon and Extreme Precipitation Events in 2017. Remote Sens. 2019, 11, 854.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top