Abstract

Abstract Smartphones with their capability to receive Global Navigation Satellite Systems (GNSS) signals can be currently considered the most common devices used for positioning tasks, including forestry applications. This study focuses on possible improvements related to two crucial changes implemented into Android smartphone positioning in the last 3 years – dual-frequency (L1/L5) GNSS receivers and the possibility of recording raw GNSS data. The study comprises three experiments: (1) real-time measurements of individual points, (2) real-time recording of trajectories, and (3) post-processing of raw GNSS data provided by the smartphone receiver. The real-time tests were conducted using final positions provided by the internal receiver, i.e. without further processing or averaging. The test on individual points has proven that the Xiaomi Mi8 smartphone with a multi-constellation, dual-frequency receiver was the only device whose accuracy was not significantly different from single-frequency mapping-grade receiver under any conditions. The horizontal accuracy of most devices was lower during leaf-on season (root mean square errors between 5.41 and 12.55 m) than during leaf-off season (4.10–11.44 m), and the accuracy was significantly better under open-area conditions (1.72–4.51 m) for all tested devices when compared with forest conditions. Results of the second experiment with track recording suggest that smartphone receivers are better suited for dynamic applications – the mean shift between reference and measured trajectories varied from 1.23 to 5.98 m under leaf-on conditions. Post-processing of the raw GNSS data in the third experiment brought very variable results. We achieved centimetre-level accuracy under open-area conditions; however, in forest, the accuracies varied from meters to tens of meters. Observed loss of the signal strength in the forest represented ~20 per cent of the open-area value. Overall, the multi-constellation, dual-frequency receiver provided more robust and accurate positional solutions compared with single-frequency smartphones. Applicability of the raw GNSS data must be further studied especially in forests, as the provided data are highly susceptible to multipath and other GNSS adverse effects.

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