As we know, forest operations can be made more environmentally friendly with different digital tools. The EFFORTE project has developed a bunch of these – see below the summary different types of tools we have developed and how can they help in operations. More detailed descriptions can be found from our recently published deliverables D4.5 Validation of developed tools for operational planning and D4.6 Validation of cost-effective and productive silviculture.

Efficient use of soil moisture maps minimizes serious damage

Depth to water maps and models (DTW maps / model) facilitate planning and decision-making on the site. The damage caused by soil compaction is biggest near water areas. The results from the test areas are good: these maps represent real wet areas with an accuracy of over 90 %. Serious damage to the soil and water areas could be avoided almost completely on the tracks when the DTW model was the base map in the forest machines. You can read more of DTW also from our deliverable D3.4 here.

The trafficability maps can help with planning of annual wheel of forest operations

In EFFORTE, development work has been carried out on both static and dynamic trafficability maps. The static trafficability map classifies the terrain according to when it is possible to operate with typical forest machines there. The map is constantly being developed, but data is already available on Metsäkeskus website ( The dynamic trafficability map is still in the test stage, but will in time provide an even more accurate tool for predicting soil bearing capacity, utilizing also the weather data. See the demo site on

Bestway and Ajourakone help to get the wood out of the forest economically and with only a little damage

Forwarding trees from the harvesting site to the landing site is a big cost in big harvesting sites, as there is a lot of traffic back and forth. It also consumes soil and contributes to nutrient lekas along the tracks, so route optimization helps not only the environment, but also the economy. Bestway (developed in Sweden) and Ajourakone (developed in Finland) use ground level and wetness models as a base and propose suitable routes and landing sites based on them. More about Bestway and Ajourakone can be found from e.g. this deliverable.

Forest machine sensors tell about the effects in real time

Forestry machines are controlled by powerful digital systems. In the future, data collected by forest machines can also be used as a tool for automatic identification of soil properties. This helps the machine operator to make better decisions when choosing routes, in order to avoid damages to the soil. One of the tools for this is CAN-bus trafficability mapping, read more about it from our deliverable D4.6!