Accuracy Assessment of GNSS-R Method for Snow Depth Detection

Selbesoğlu M. O. , Akpınar B. , Yavaşoğlu H. H. , Karabulut M. F. , Aykut N. O. , Gülal V. E.

International Symposium on Applied Geoinformatics (ISAG-2019) , İstanbul, Türkiye, 7 - 09 Kasım 2019, ss.81

  • Yayın Türü: Bildiri / Özet Bildiri
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.81


Nowadays, the GNSS system (Global Satellite Based Positioning System) usage area has significantly expanded and has become an effective tool in various important applications such as GNSS meteorology, GNSS Reflectometry and GNSS Radio Occultation. The ability of enhanced GNSS methods not only provides high accurate positioning information but also contributes to the applications for determining the important quantities such as precipitable water vapour, sea/snow/ice level changes, wind speed, soil moisture etc.). The tropospheric signal delay effect is a source of error for precise navigation and positioning, but also allows information about the troposphere in terms of humidity, temperature and water vapour. The examination of the signal path between the satellite and the receiver allows us to obtain information about the atmospheric layers through where the signal passes. On the other hand, changes in the height of snow and ice masses have significant physical impact on the earth's crust, and the monitoring of these changes can be achieved by the fluctuations in the power of the signals that are reflected after the GNSS signals come to Earth surface. GNSS radio signals in L-band (1.2 and 1.5 GHz) are reflected from water/ice surfaces as scattered radio waves and can be used for monitoring height variations. If the surface (ground or snow) is quite flat, the SNR data is a sine wave. The frequency of the sine wave informs how far the reflective surface is. In accordance with these information that the GNSS system can contribute to the geophysical studies as well as positioning applications (cartography, bathymetric, position sensitivity, navigation etc.) by processing the signals by various analysing approaches. The purpose and motivation of the study was to analysing the performance of GNSS-R method for detecting the snow depth in varying temporal, spatial and seasonal conditions. For the study, two different permanent GNSS station’s observation data was collected from SOPAC and analysed to determine snow depths. The validation of the results was carried out by comparing GNSS-R snow depth data with Snowpack Telemetry (SNOTEL) Network’s snow depth data. As the result, accuracy of the GNSS-R method for these stations and conditions were determined.