MOTI is a smartphone application that enables users to record quantitative data on what they see in the forest with just a few clicks – especially the wood stock, basal area, number of trees per hectare and growth increment. Try to estimate these key figures for the scene in figure 2, taking the person in the middle of the picture as a reference.
Without experience, making such estimates is anything but simple. One of the main goals of MOTI is to help users train their eyes to improve their personal assessments by being able to measure these figures quickly and easily. The app is also intended to provide decision support in the field (for marking, planning of silvicultural interventions…).
With MOTI, single or clustered sample plots in a stand can be measured and even local inventories performed (e.g. one sample plot every 100 m). The statistical error is then continuously computed. The app also includes a growth model for simulating the medium-term development of the investigated stand. The data collected is saved on a server and can later be downloaded from the office in Excel format.
MOTI enables the user to determine the basal area per ha (G) according to the Bitterlich-method (angular count method), to record the number of trees per ha (N) in circular sample plots and to measure tree height (h). In the "settings" register, symbolized by a screwdriver (see fig. 3), the user can freely choose the counting factor (k) to estimate G, the plot size to determine N, as well as the height of the markers to measure N and h.
As the following brief instructions show, the measurements are relatively easy to make:
- Determining the basal area using MOTI
- Determining the number of stems per ha using MOTI
- Determining tree height using MOTI
You will probably need an hour or two of practice to learn the procedure and obtain reliable values for G, N and h. For good results, the smartphone must be calibrated beforehand. The integrated calibration assistant leads the user through the process, which takes around 15 minutes. The calibration needs to be done only once after the initial installation of the application.
Figure 4 shows the evaluation of the measurements taken with MOTI in the stand shown in figure 2. The application gives the results of the measurements, as well as additional information concerning wood stock and the diameter of the mean basal area stem (dg). If several records were taken in one stand, the statistical margin of error is also displayed. A built-in GPS function allows the coordinates of each sample plot to be recorded and saved.
Innovations in MOTI are not limited to the survey of forest inventory data. Built into the app is also SiWaWa: a simple and effective simulation model that provides information about forest growth. For this model to compute, in less than a second, the development of the forest area under study, the only input data needed is precisely what MOTI records - namely G, N and hdom (dominant height).
SiWaWa provides information about the growth increment, timber stock development, mortality and the stem distribution in DBH-classes. Up until now, this function has been limited to uniform beech, spruce, ash and sycamore stands in Switzerland (where the proportion of dominant tree species is at least 85%).
MOTI compares well with conventional appliances. For one thing, using a smartphone definitely has many advantages: the comparably high photosensitivity of its optics, the bright display, the zoom function, the way it can automatically take slopes into consideration with the help of the integrated sensors, and the possibility of simplifying and evaluating the measurements on the spot using an intuitive graphical user-interface.
The app prevents the user losing count while doing a stem count, especially when recording different tree species. Moreover, the measurement data does not have to be recorded several times because the app is synchronized with an online server and can be downloaded at any time.
Experiments carried out during the MOTI research and development project indicate that the results for the basal area using MOTI are as good as those with Bitterlich-relascope, if not more accurate. During these tests the basal area G was measured 96 times in four different stands (deciduous and coniferous, pole stage forest and timber forest) with both MOTI and the relascope. If the results were mixed, the problematic trees were identified and the source of the error analyzed. MOTI is not as precise as a Vertex in determining tree height, but close to: The deviation was less than 6% in 75% of the cases investigated. Other pros of MOTI are that this tool does not require large material investments as only a smartphone and a marker are required.
In a study in the mountainous area of Canton Valais, Wendeling (2014) found MOTI had some drawbacks: the display was not very legible in direct sunlight or with high contrast weather conditions; focusing on a tree was difficult if the underwood was dense and formed the bulk part of the foreground; and it was difficult to measure the tree height if the stem was not clearly visible.
Legibility in direct sunlight depends on the type of smartphone used. With newer models this problem has been solved.
Where to get MOTI?
MOTI can be downloaded free of charge from Google Play (Android), from the App Store (iPhone) or from www.moti.ch. The project's website also includes a help section as well as various descriptions. The application is available in English, German, French and Italian.
Who’s behind MOTI?
MOTI is the result of a research and development project operated by the School of Agricultural, Forest and Food Sciences (HAFL) in cooperation with the department Engineering and Information Technology at Bern University of Applied Sciences (BFH). It was financed by the Forest and Wood Research Fund, by the Federal Office for the Environment (FOEN) and by the following Swiss cantons: ZH, LU, FR, SO, BS, BL, SG, GR, TI, VD, VS and GE.
A new version for tablets and new inventory methods are currently being developed within the framework of the EU project FOCUS.
Translation: Julian Muhmenthaler (HAFL)