Intercomparison of Soil Moisture Retrieved from GNSS-R and from Passive L-Band Radiometry at the Valencia Anchor Station

Details

• Journal Title:
  Sensors
• Personal Author:
  Yin, Cong ; Lopez-Baeza, Ernesto ; Martin-Neira, Manuel ; Fernandez-Moran, Roberto ; Yang, Lei ; Navarro-Camba, Enrique A. ; Egido, Alejandro ; Mollfulleda, Antonio ; Li, Weiqiang ; Cao, Yunchang ; Zhu, Bin ; Yang, Dongkai
• NOAA Program & Office:
  NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research)
• Description:
  In this paper, the SOMOSTA (Soil Moisture Monitoring Station) experiment on the intercomparison of soil moisture monitoring from Global Navigation Satellite System Reflectometry (GNSS-R) signals and passive L-band microwave radiometer observations at the Valencia Anchor Station is introduced. The GNSS-R instrument has an up-looking antenna for receiving direct signals from satellites, and a dual-pol down-looking antenna for receiving LHCP (left-hand circular polarization) and RHCP (right-hand circular polarization) reflected signals from the soil surface. Data were collected from the three different antennas through the two channels of Oceanpal GNSS-R receiver and, in addition, calibration was performed to reduce the impact from the differing channels. Reflectivity was thus measured, and soil moisture could be retrieved. The ESA (European Space Agency)-funded ELBARA-II (ESA L Band Radiometer II) is an L-band radiometer with two channels with 11 MHz bandwidth and respective center frequencies of 1407.5 MHz and 1419.5 MHz. The ELBARAII antenna is a large dual-mode Picket horn that is 1.4 m wide, with a length of 2.7 m with −3 dB full beam width of 12° (±6° around the antenna main direction) and a gain of 23.5 dB. By comparing GNSS-R and ELBARA-II radiometer data, a high correlation was found between the LHCP reflectivity measured by GNSS-R and the horizontal/vertical reflectivity from the radiometer (with correlation coefficients ranging from 0.83 to 0.91). Neural net fitting was used for GNSS-R soil moisture inversion, and the RMSE (Root Mean Square Error) was 0.014 m3/m3. The determination coefficient between the retrieved soil moisture and in situ measurements was R2 = 0.90 for Oceanpal and R2 = 0.65 for Elbara II, and the ubRMSE (Unbiased RMSE) were 0.0128 and 0.0734 respectively. The soil moisture retrievals by both L-band remote sensing methods show good agreement with each other, and their mutual correspondence with in-situ measurements and with rainfall was also good.
• Keywords:
  Quantitative Research Radiometers Reflectometer Remote Sensing Soil Moisture Quantitative Research Remote Sensing Soil Moisture
• Source:
  Sensors (Basel); 19(8): 1-16
• DOI:
  https://doi.org/10.3390/s19081900
• Pubmed Central ID:
  PMC6515244
• Document Type:
  Journal Article
• Place as Subject:
  Valencia (Spain)
• Rights Information:
  CC BY
• Compliance:
  PMC
• Main Document Checksum:
  urn:sha-512:4175ba82b6de12a489d0c5c46889117cd2106fb745fcf9edf0b6e9fbf8243ec3f4fc1b41963ac81bbdad2c2dab3f853e18f03afb9ef8310b17771498f30370a9
• Download URL:
  https://repository.library.noaa.gov/view/noaa/25626/noaa_25626_DS1.pdf
• File Type:
  [PDF - 6.50 MB ]