UDC: 
DOI: 
10.22389/0016-7126-2024-1010-8-23-30
1 Shevchuk R.V.
2 Manevich A.I.
3 Losev I.V.
4 Aleshin I.M.
5 Akmatov D.Zh.
6 Tatarinova T.A.
7 Urmanov D.I.
Year: 
№: 
1010
Pages: 
23-30

RAS Geophysical Center

1, 
2, 
3, 
4, 
5, 
6, 
7, 
Abstract:
The authors present the results of studying the forest cover impact on the measurements accuracy made with the help of global navigation satellite systems at local geodynamic test sites. The study was held at the Nizhne-Kansk geodynamic polygon (Krasnoyarsk krai) in the period from 2010 to 2023. The main purpose was to investigate the wood vegetation influencing the GNSS measurements accuracy. Three classes of forest cover were defined: high density (class 1), moderate thickness (class 2), and ideal dimensional conditions (class 3). The results showed that the greatest errors occur at high forest density, both in plane and altitude. To improve the exactness, increasing the duration of the process and selecting areas with lower density of forest cover is recommended. Planning field works taking into account the class and time enables improving the accuracy of GNSS measurements significantly, which is especially important for geodynamic studies that require high precision of geodetic points coordinates
This work was conducted in the framework of budgetary funding of the of the Sсhmidt institute of physics of the Earth of the RAS, adopted by the Ministry of Science and Higher Education of the Russian Federation
References: 
1.   Basmanov A. V. Geodezicheskii monitoring Baikal'skogo geodinamicheskogo poligona Rosreestra. Vestnik SGUGiT, 2015, no. 2 (30), pp. 48–55.
2.   Galaganov O.N., Guseva T.V., Krupennikova I.S. Sopostavlenie dannykh GLONASS i GPS-izmerenii sposobom differentsial'nogo pozitsionirovaniya v rezhime statika pri reshenii geodinamicheskikh zadach. Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2015, Vol. 12, no. 4, pp. 28–37.
3.   Kaftan V.I., Tatarinov V.N., Shevchuk R.V., Manevich A.I., Kaftan A.V. (2023) Experimental study of the field methodology for assessing the accuracy of GNSS measurements. Geodezia i Kartografia, 84(10), pp. 12-21. (In Russian). DOI: 10.22389/0016-7126-2023-1000-10-12-21.
4.   Kaftan V. I., Ustinov A. V. Povyshenie tochnosti lokal'nogo geodinamicheskogo monitoringa sredstvami global'nykh navigatsionnykh sputnikovykh sistem. Gornyi zhurnal, 2015, no. 10, pp. 32–38. DOI: 10.17580/gzh.2015.10.06.
5.   Kosarev N.S., Shcherbakov A.S. Statisticheskij analiz tochnosti opredeleniya polozhenij sputnikov sistem GLONASS i GPS. Vestnik SGGA, Novosibirsk: SGGA, 2014, 2 (26). pp. 9–18.
6.   Perminov A. Yu., Morozov D. A., Kupriyanov A. O. Eksperimental'naya aprobatsiya metodiki opredeleniya vliyaniya mnogoluchevosti na kodovye i fazovye izmereniya po signalam GNSS. Izvestia vuzov. Geodesy and Aerophotosurveying, 2022, Vol. 66, no. 5, pp. 6–13.
7.   Prikhoda A. G., Lapko A. P., Shevchuk S. O., Mal'tsev G. I. Navigatsionno-geodezicheskoe obespechenie geologo-geofizicheskikh rabot s ispol'zovaniem global'nykh sputnikovykh sistem GLONASS i GPS. KiberLeninka: nauchnaya elektronnaya biblioteka, 2011, URL: https://clck.ru/3CRsd6 (accessed: 25.02.2024).
8.   Tereshchenko V. E. Analiz kachestva sputnikovykh izmerenii s pomoshch'yu programmnoi utility TEQC. Vestnik SSUGT, 2020, Vol. 25, no. 3, pp. 72–88. DOI: 10.33764/2411-1759-2020-25-3-72-88.
9.   Shirokii S. M., Titov E. V. O sposobe povysheniya tochnosti navigatsii potrebitelei GLONASS s ispol'zovaniem adaptivnoi modeli troposfery, peredavaemoi v navigatsionnom soobshchenii. Trudy Instituta prikladnoi astronomii RAN, 2013, 27. pp. 326–333.
10.   Akbulut R., Ucar Z., Bettinger P., Merry K., Obata S. (2017) Effects of forest thinning on static horizontal positions collected with a mapping-grade GNSS receiver. Mathematical and Computational Forestry and Natural-Resource Sciences, no. 9 (1), pp. 14–21.
11.   Bastos A. S., Hasegawa H., Yoshimura T. (2013) GPS Accuracy in Using Antenna Pole under Tree Canopies and Usability of Signal Interruption Probability (SIP) for Accuracy Estimation. Journal of The Japan Forest Engineering Society, no. 28 (3), pp. 181–186.
12.   Bohm J., Moller G., Schindelegger M., Pain G., Weber R. (2015) Development of an improved empirical model for slant delays in the troposphere (GPT2w). GPS Solutions, no. 19 (3), pp. 433–441. DOI: 10.1007/s10291-014-0403-7.
13.   Ding W., Teferle F. N., Kazmierski K., Laurichesse D., Yuan Y. (2017) An evaluation of real-time troposphere estimation based on GNSS Precise Point Positioning. Journal of Geophysical Research-Atmospheres, no. 122 (5), pp. 2779–2790. DOI: 10.1002/2016JD025727.
14.   Jgouta M., Nsiri B. (2015) Statistical Estimation of GNSS Pseudo-Range Errors. Procedia Computer Science, no. 73, pp. 258–265. DOI: 10.1016/j.procs.2015.12.027.
15.   Leandro R., Santos M., Langley R. (2006) UNB Neural Atmosphere Models. Development and Performance. Proceedings of ION NTM. Monterey, California, USA. pp. 564–573.
16.   Næsset E. (1999) Point accuracy of combined pseudorange and carrier phase differential GPS under forest canopy. Canadian Journal of Forest Research, no. 29, pp. 547–553.
17.   Rabaoui A., Viandier N., Duflos E., Marais J., Vanheeghe P. (2012) Dirichlet Process Mixtures for Density Estimation in Dynamic Nonlinear Modeling: Application to GPS Positioning in Urban Canyons. IEEE Transactions on Signal Processing, no. 60, pp. 1638–1655.
18.   Richards P. G., Voglozin D. (2011) Reexamination of ionospheric photochemistry. Journal of Geophysical Research, no. 116: A08307, DOI: 10.1029/2011JA016613.
Citation:
Shevchuk R.V., 
Manevich A.I., 
Losev I.V., 
Aleshin I.M., 
Akmatov D.Zh., 
Tatarinova T.A., 
Urmanov D.I., 
(2024) Analysis of the radio interference and measurement parameters impact on GNSS accuracy in forested areas. Geodesy and cartography = Geodezia i Kartografia, 85(8), pp. 23-30. (In Russian). DOI: 10.22389/0016-7126-2024-1010-8-23-30