The GNSS (Global Navigation Satellite System) receivers are commonly used in forest management in order to determine objects coordinates, area or length assessment and many other tasks which need accurate positioning. Unfortunately, the forest structure strongly limits access to satellite signals, which makes the positioning accuracy much weak comparing to the open areas. The main reason for this issue is the multipath phenomenon of satellite signal. It causes radio waves reflections from surrounding obstacles so the signal do not reach directly to the GNSS receiver’s antenna. Around 50% of error in GNSS positioning in the forest is because of multipath effect. In this research study, an attempt was made to quantify the forest stand features that may influence the multipath variability. The ground truth data was collected in six Forest Districts located in different part of Poland. The total amount of data was processed for over 2,700 study inventory plots with performed GNSS measurements. On every plot over 25 forest metrics were calculated and over 25 minutes of raw GNSS observations (1500 epochs) were captured. The main goal of this study was to find the way of multipath quantification and search the relationship between multipath variability and forest structure. It was reported that forest stand merchantable volume is the most important factor which influence the multipath phenomenon. Even though the similar geodetic class GNSS receivers were used it was observed significant difference of multipath values in similar conditions.
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 (MCFNS), 9 (1), 14–21.
Al-Shaery, A., Zhang, S., Rizos, C. 2013. An enhanced calibration method of GLONASS inter-channel bias for GNSS RTK. GPS Solutions, 17 (2), 165–173.
Bakula, M., Przestrzelski, P., Kazmierczak, R. 2015. Reliable Technology of Centimeter GPS/GLO-NASS Surveying in Forest Environments. IEEE Transactions on Geoscience and Remote Sensing, 53 (2), 1029–1038.
Bastos, A.S., Hasegawa, H. 2013. Behavior of GPS signal interruption probability under tree canopies in different forest conditions. European Journal of Remote Sensing, 46 (1), 613–622.
Bettinger, P., Merry, K. 2012. Static horizontal positions determined with a consumer-grade GNSS receiver: One assessment of the number of fixes necessary. Croatian Journal of Forest Engineering, 33 (1), 149–157.
Bettinger, P., Merry, K. 2018. Follow-up study of the importance of mapping technology knowledge and skills for entry-level forestry job positions, as deduced from recent job advertisements. Mathematical and Computational Forestry and Natural-Resource Sciences (MCFNS), 10 (1), 15–23.
Blum, R., Bischof, R., Sauter, U.H., Foeller, J. 2016. Tests of reception of the combination of GPS and GLONASS signals under and above forest canopy in the Black Forest, Germany, using choke ring antennas. International Journal of Forest Engineering, 27 (1), 2–14.
Bosy, J., Graszka, W., Leończyk, M. 2007. ASG-EU-POS-a multifunctional precise satellite positioning system in Poland. European Journal of Navigation, 5 (4), 2–6.
Brach, M., Zasada, M. 2014. The effect of mounting height on GNSS receiver positioning accuracy in forest conditions. Croatian Journal of Forest Engineering, 35 (2), 245–253.
Breiman, L., Friedman, J., Stone, C.J., Olshen, R.A. 1999. Classification and regression trees. Chapman and Hall/CRC, Boca Raton.
Cheng, C., Pan, Q., Calmettes, V., Tourneret, J.-Y. 2016a. A maximum likelihood-based unscented Kalman filter for multipath mitigation in a multi-correlator based GNSS receiver. In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 6560–6564.
Cheng, C., Tourneret, J.-Y., Pan, Q., Calmettes, V. 2016b. Detecting, estimating and correcting multipath biases affecting GNSS signals using a marginalized likelihood ratio-based method. Signal Processing, 118, 221–234.
Closas, P., Fernandez-Prades, C., Fernandez-Rubio, J.A. 2009. A Bayesian approach to multipath mitigation in GNSS receivers. IEEE Journal of Selected Topics in Signal Processing, 3 (4), 695–706.
Danskin, S., Bettinger, P., Jordan, T. 2009a. Multipath mitigation under forest canopies: A choke ring antenna solution. Forest Science, 55 (2), 109–116.
Danskin, S.D., Bettinger, P., Jordan, T.R., Cieszewski, C. 2009b. A comparison of GPS performance in a southern hardwood forest: Exploring low-cost solutions for forestry applications. Southern Journal of Applied Forestry, 33 (1), 9–16.
Dogan, U., Uludag, M., Demir, D.O. 2014. Investigation of GPS positioning accuracy during the seasonal variation. Measurement, 53, 91–100.
Erfanifard, Y., Stereńczak, K., Kraszewski, B., Kamińska, A. 2018. Development of a robust canopy height model derived from ALS point clouds for predicting individual crown attributes at the species level. International Journal of Remote Sensing, 39 (23), 9206–9227.
Estey, L.H., Meertens, C.M. 1999. TEQC: the multi-purpose toolkit for GPS/GLONASS data. GPS Solutions, 3 (1), 42–49.
Fassnacht, F.E., Latifi, H., Hartig, F. 2018. Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR. Remote Sensing of Environment, 213, 115–128.
Frank, J., Wing, M.G. 2014. Balancing horizontal accuracy and data collection efficiency with mapping-grade GPS receivers. Forestry, 87 (3), 389–397.
Giremus, A., Tourneret, J.-Y., Calmettes, V. 2007. A particle filtering approach for joint detection/estimation of multipath effects on GPS measurements. IEEE Transactions on Signal Processing, 55 (4), 1275–1285.
Gower, S.T., Kucharik, C.J., Norman, J.M. 1999. Direct and indirect estimation of leaf area index, fAPAR, and net primary production of terrestrial ecosystems. Remote Sensing of Environment, 70 (1), 29–51.
Groves, P.D., Jiang, Z., Rudi, M., Strode, P. 2013. A portfolio approach to NLOS and multipath mitigation in dense urban areas. In: Proceedings of the 26th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2013), 3231 – 3247. The Institute of Navigation, Manassas, USA.
Gurtner, W., Estey, L. 2007. RINEX the receiver independent exchange format. Werner Gurtner Astronomical Institute University of Bern.
Hapgood, M. 2017. Satellite navigation-Amazing technology but insidious risk: Why everyone needs to understand space weather. Space Weather, 15 (4), 545–548.
Hasegawa, H., Yoshimura, T. 2003. Application of dual-frequency GPS receivers for static surveying under tree canopies. Journal of Forest Research, 8 (2), 103–110.
Hilla, S., Cline, M. 2004. Evaluating pseudorange multipath effects at stations in the National CORS Network. GPS Solutions, 7 (4), 253–267.
Hofmann-Wellenhof, B., Lichtenegger, H., Wasle, E. 2008. GNSS--global navigation satellite systems: GPS, GLONASS, Galileo, and more. Springer, Wien, New York.
Holden, N.M., Martin, A.A., Owende, P.M.O., Ward, S.M. 2001. A method for relating GPS performance to forest canopy. International Journal of Forest Engineering, 12 (2), 51–56.
Holopainen, M. et al. 2014. Outlook for the next generation’s precision forestry in Finland. Forests, 5 (7), 1682–1694.
Irsigler, M. 2010. Characterization of multipath phase rates in different multipath environments. GPS Solutions, 14 (4), 305–317.
Jgouta, M., Nsiri, B. 2015. Statistical estimation of GNSS pseudo-range errors. Procedia Computer Science, 73, 258–265.
Kaartinen, H. et al. 2015. Accuracy of kinematic positioning using global satellite navigation systems under forest canopies. Forests, 6 (9), 3218–3236.
Kamińska, A., Lisiewicz, M., Stereńczak, K., Kraszewski, B., Sadkowski, R. 2018. Species-related single dead tree detection using multi-temporal ALS data and CIR imagery. Remote Sensing of Environment, 219, 31–43.
Kursa, M.B., Rudnicki, W.R. 2010. Feature selection with the Boruta package. Journal of Statistical Software, 36 (11).
Le Dantec, V., Dufrêne, E., Saugier, B. 2000. Interannual and spatial variation in maximum leaf area index of temperate deciduous stands. Forest Ecology and Management, 134 (1/3), 71–81.
Li, X. et al. 2015. Precise positioning with current multi-constellation Global Navigation Satellite Systems: GPS, GLONASS, Galileo and BeiDou. Scientific Reports, 5 (1).
Liang, X. et al. 2014. Possibilities of a personal laser scanning system for forest mapping and ecosystem services. Sensors, 14 (1), 1228–1248.
Liaw, A., Breiman, L., Cutler, A., Wiener, M. 2018. Package ‘randomForest’.
Liu, J. et al. 2016. Can global navigation satellite system signals reveal the ecological attributes of forests? International Journal of Applied Earth Observation and Geoinformation, 50, 74–79.
Liu, J. et al. 2017. A novel GNSS technique for predicting boreal forest attributes at low cost. IEEE Transactions on Geoscience and Remote Sensing, 55 (9), 4855–4867.
Luo, S. et al. 2017. Fusion of airborne LiDAR data and hyperspectral imagery for aboveground and below-ground forest biomass estimation. Ecological Indicators, 73, 378–387.
McGaughey, R.J., Ahmed, K., Andersen, H.-E., Reutebuch, S.E. 2017. Effect of occupation time on the horizontal accuracy of a mapping-grade GNSS receiver under dense forest canopy. Photogrammetric Engineering and Remote Sensing, 83 (12), 861–868.
Mielcarek, M., Stereńczak, K., Khosravipour, A. 2018. Testing and evaluating different LiDAR-derived canopy height model generation methods for tree height estimation. International Journal of Applied Earth Observation and Geoinformation, 71, 132–143.
Miścicki, S., Stereńczak, K. 2013. A two-phase inventory method for calculating standing volume and tree-density of forest stands in central Poland based on airborne laser-scanning data. Leśne Prace Badawcze, 74 (2), 127–136.
Olpenda, A., Stereńczak, K., Będkowski, K. 2018. Modeling solar radiation in the forest using remote sensing data: a review of approaches and opportunities. Remote Sensing, 10 (5), 694.
Paziewski, J., Wielgosz, P. 2014. Assessment of GPS + Galileo and multi-frequency Galileo single-epoch precise positioning with network corrections. GPS Solutions, 18 (4), 571–579.
Pirsiavash, A. et al. 2017. Characterization of signal quality monitoring techniques for multipath detection in GNSS applications. Sensors, 17 (7), 1579.
Pirti, A. 2016. The seasonal effects of deciduous tree foliage in CORS-GNSS measurements (VRS/FKP). Tehnički vjesnik, 23 (3), 769–774.
R Core Team. 2013. R: a language and environment for statistical computing. R foundation for statistical computing. Vienna, Austria.
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, 60 (4), 1638–1655.
Rai, B. 2017. Feature selection and predictive modeling of housing data using random forest. International Journal of Industrial and Systems Engineering, 11 (4), 5.
Robakowski, P., Wyka, T., Samardakiewicz, S., Kierzkowski, D. 2004. Growth, photosynthesis, and needle structure of silver fir (Abies alba Mill.) seedlings under different canopies. Forest Ecology and Management, 201 (2/3), 211–227.
Sigrist, P., Coppin, P., Hermy, M. 1999. Impact of forest canopy on quality and accuracy of GPS measurements. International Journal of Remote Sensing, 20 (18), 3595–3610.
Stereńczak, K., Moskalik, T. 2015. Use of LIDAR-based digital terrain model and single tree segmentation data for optimal forest skid trail network. IForest – Biogeosciences and Forestry, 8 (5), 661–667.
Stereńczak, K., Kraszewski, B., Mielcarek, M., Piasecka, Ż. 2017. Inventory of standing dead trees in the surroundings of communication routes – The contribution of remote sensing to potential risk assessments. Forest Ecology and Management, 402, 76–91.
Strobl, C., Boulesteix, A.-L., Zeileis, A., Hothorn, T. 2007. Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinformatics, 21.
Suski, W. 2012. A study of environment noise in ultra-wideband indoor position tracking. Ph.D. dissertation, Clemson University.
Szostak, M., Wężyk, P. 2013. Pomiary GNSS w przestrzeni leśnej przy wykorzystaniu różnej klasy odbiorników oraz wybranych trybów pomiaru. Archives of Photogrammetry, Cartography and Remote Sensing, 25.
Szostak, M., Bednarski, A., Wężyk, P. 2018. Monitoring of secondary forest succession on abandoned farmland using LiDAR point clouds. Commitee on Geodesy PAS.
Teng, Y., Huang, Q., Ao, Y., Li, Y. 2016. A closed-form method for single-point positioning with six satellites in dual-GNSS constellations. Advances in Space Research, 58 (11), 2280–2286.
Titouni, S., Rouabah, K., Atia, S., Flissi, M., Khababa, O. 2017. GNSS multipath reduction using GPS and DGPS in the real case. Positioning, 08 (04), 47–56.
Topcon Inc. 2013. MAGNET Tools 2.0 Help. Topcon Positioning Systems, Inc. Rev A 1000412 01, 276.
Ucar, Z., Bettinger, P., Weaver, S., Merry, K.L., Faw, K. 2014. Dynamic accuracy of recreation-grade GPS receivers in oak-hickory forests. Forestry, 87 (4), 504–511.
Unger, D.R. et al. 2013. Accuracy assessment of perimeter and area calculations using consumer-grade global positioning system (GPS) units in southern forests. Southern Journal of Applied Forestry, 37 (4), 208–215.
Wang, M. et al. 2018a. Comparison of three methods for estimating GPS multipath repeat time. Remote Sensing, 10 (2), 6.
Wang, Y. et al. 2018b. Statistical multipath model based on experimental GNSS data in static urban canyon environment. Sensors, 18 (4), 1149.
Weaver, S.A., Ucar, Z., Bettinger, P., Merry, K. 2015. How a GNSS receiver is held may affect static horizontal position accuracy. PLoS One, 10 (4), e0124696.
Weill, L.R. 2003. Multipath mitigation: How good can it get with new signals? GPS World, 14 (6), 106–113.
Wężyk, P. 2004. Mity i fakty dotyczące stosowania GPS w leśnictwie. Roczniki Geomatyki-Annals of Geomatics, 2 (4), 14.
Wright, W., Wilkinson, B., Cropper, W. 2018. Development of a GPS forest signal absorption coefficient index. Forests, 9 (5), 226.
Wright, W.C., Wilkinson, B.E., Cropper, W.P. 2017. Estimating signal loss in pine forests using hemispherical sky oriented photos. Ecological Informatics, 38, 82–88.
Ziedan, N.I. 2011. Multi-frequency combined processing for direct and multipath signals tracking based on particle filtering. Proceedings of the 24th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS 2011), 21–23.
Zimbelman, E.G., Keefe, R.F. 2018. Real-time positioning in logging: Effects of forest stand characteristics, topography, and line-of-sight obstructions on GNSS-RF transponder accuracy and radio signal propagation. PLoS One, 13 (1), e0191017.