Akademik Veri Yönetim Sistemi
International Symposium on Applied Geoinformatics (ISAG-2019) , İstanbul, Türkiye, 7 - 09 Kasım 2019, 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.