“It is surprising that many Pygmy hunter-gatherers in the Congo Basin, though unable to read the numbers on banknotes or write their own names, have begun to use handheld computers attached to global positioning systems (GPS).” (Lewis, 2012)
The above quotation refers to the work that Jerome Lewis started in 2005, when he established a scheme in which indigenous, forest-dwelling communities play an active role in the monitoring of logging activity. In our current work, based on this earlier project, we aim to enable communities to accurately map important resources they want to claim and protect from destruction. Therefore we develop an end-to-end solution for the collection, transmission, storage, visualisation, editing and sharing of geo-referenced data.
A minimum of four satellites are required to determine a 3D location. Despite the five to ten satellites, which are typically in visible range, the radio signal emitted by the satellites are too weak to penetrate dense vegetation, which makes it difficult to get accurate position fixes in places like tropical rainforests.
During our field trip to the Republic of Congo in April/May 2013 we conducted an experiment to test whether we can get adequate GPS location fixes under the dense tree canopy. We were equipped with two smartphones (Samsung Galaxy Xcover, Samsung Galaxy S2), two handheld GPS receivers which were kindly provided by Trimble (Trimble Juno SC, Trimble Juno SD) as well as a Leica Zeno 10, which is advertised to obtain sub-meter accuracy in real time. For this preliminary test we captured GPS positions at ten different locations with varying forest density. The aim was to get five GPS fixes for each device at each location. Apart from the Trimble Juno 3D, which could not find signal at two of the locations, all the GPS receivers resolved a location fix in less than a minute. In absence of a known location which serves as a reference point we compare the obtained positions with each other.
The map shows the positional mean per location per device. The circle represents the distribution of these means as the first standard deviation. Point 7 and point 9 show very high spatial distributions. It is noticeable that the position fixes obtained by the Trimble Juno 3D is often far off the positions obtained by the other devices, so we are exploring if it might be some fault in this specific unit. The following table shows the maximum distances between the averaged measurements per location. Due to the issues that we noted above with the data acquired by the Trimble Juno 3D, we omitted these data from further calculations, resulting in a significant decrease of distances (see following table).
The primary goal of the described experiment was to get an idea of obtainable GPS accuracies by low-cost devices under local conditions. It surprised us how little time it took for the devices to find a location fix, even after rebooting. The results we got from our experiment show that the positional (horizontal) errors are most likely in the range of 10-30 metres, which is about what we expected. We aim to carry out further tests in the coming months to validate these first results, and to understand the range of devices that are suitable for forest work
Lewis, J. (2012): Technological leap-frogging in the Congo Basin. Pygmies and geographic positioning systems in Central Africa: What has happened and where is it going? African Study Monographs , Supplementary Issue 43: 15-44