SUSTAINABLE FOREST MANAGEMENT AND PLANNING USING DEPTH-TO-WATER MAPS: PART 2
Part 2 of the three-part blog series explains the Depth-To-Water (DTW) maps which TECH4EFFECT used to identify sensitive soils and sites for environmental conservation across four countries.
Trafficability maps to reduce site impact
Part 1 of the blog examined the importance of forest machines in delivering on production efficiency goals and improved safety in harvesting operations. An increase in mechanized harvesting has drawn more attention to the importance of soil protection over the last decades, especially in wet conditions, in an effort to minimize compaction and rutting.
It is essential to plan and prepare a harvesting operation properly, which means having detailed knowledge of the on-site conditions that determine the trafficability of the site. High trafficability means that the machine can gain access to the site because the soils are stable. Low trafficability indicates unfavourable conditions to carry out a harvesting operation. Adhering to these bearing capacity predictions, amongst other things, is vital to ensure ecologically sound harvesting operations.
Numerous methods are available for generating trafficability maps and each has specific benefits and drawbacks. All of these can be uploaded to a live display on the machine and are used to alert machine operators to sensitive soils, or ecological sites which should be avoided during harvesting.
Convincing operators key to map utilisation
However, in many European countries, there is no common system to assess the risk of severe environmental impacts on the soil. As a result, such solutions are poorly implemented in every-day operations. Contractors also often move between regions, which further complicates the process, with an operator needing to access several maps in one day.
For a forest machine operator, one of the highest priorities is to maximize production, where working speed is essential to optimize the profitability of their tasks. One of the biggest challenges in implementing trafficability modelling systems lies in encouraging operators to upload and utilize maps in the first place. To do this, they must be convinced of the benefits.
DTW maps proven effective for protecting soil
It was against this backdrop that the TECH4EFFECT (T4E) project examined several of the existing methods available and identified a promising approach, using DTW maps (Figure 1, above). The DTW-algorithm, which was developed by Murphy et al. (2009; 2011; 2007) at the University of New Brunswick, Canada, was selected by T4E for use as the main method for modelling terrain trafficability to identify wet soils (Figure 2, below).
Over the last few years, DTW maps have been used mainly by innovative European entrepreneurs and operators. Their use is gaining in popularity, and DTW maps are now being used by state forestry institutions and large forest owners’ associations across Scandinavia, which have a long history of forest engineering and innovative practices. Through T4E, it is both hoped and envisaged that they will be taken up by forestry on a wider European scale in ensuring that the operator has a good overview and that environmental best practices are adhered to.
How are DTW maps created?
Specific institutions, including government agencies, map the topography of the earth from aeroplanes or helicopters, using aerial laser scanning technologies (ALS). This ground surface representation data is then often made available (commercially or open source) for further use and serves as the underlying data set for the creation of a DTW map and its applications in forestry.
The DTW algorithm is based on a grid of water flow accumulation in conjunction with a grid of slope values and ultimately provides a single number for any point in the terrain. This number reflects the Depth-To-Water, which essentially identifies points of lower drainage, indicating a higher probability for wetness at that point (Figure 2, above). Such an area typically has a lower bearing capacity than its immediate surroundings.
T4E mapping – four case studies
T4E acquired digital elevation models for study sites in Finland, Germany, Norway and Poland, each covering an area of approximately 50 km² (Figure 3, above). The models were generated from ALS data with a resolution of between 0.25 and 1 datapoint per m2 of ground. Using this data, the University of New Brunswick assisted in generating DTW maps with four different flow initiation areas, each representing different seasonal conditions (Figure 3, above).
Monthly measurements were performed over one year, capturing seasonal effects and changing operational conditions (Figure 4, right). These results can be used to adapt the DTW-maps to changing conditions and site effects.
Preliminary results show a high overlap of low soil bearing capacity with areas already predicted to be sensitive, according to the DTW-index. These findings have encouraged T4E researchers to further elaborate the algorithm and implement it in every-day-use of forest operations.
Wider implications for road construction
To further improve the utility of the trafficability maps, they were also analysed against other important information from road maps, forest inventory maps, habitats and ecologically sensitive areas. The output of this also allowed for an assessment of other elements than site trafficability.
For example, due to geomorphological patterns, forest roads at the German study site tendentially followed shallow valleys, which showed bad drainage according to the DTW-index. Positioning forest roads on areas with low soil bearing capacity and frequently wet conditions may have led to high costs during construction as well as maintenance.
T4E partner Georg-August-Universität Göttingen has published the results of these first analyses of trafficability maps in Public Deliverable (D4.1) “Terrain Accessibility for 4 Case Study Areas” (Schönauer et al. 2019).
T4E Mapping App to be examined in Part 3
In the final blog of the three-part series examining digital terrain models, the freely available T4E Mapping App will be presented with an explanation of how it can be used in a practical harvesting operation. T4E identified the need to develop solutions that work across platforms (currently one of the limiting factors of increased digital measures for data transmission), to more accurately guide harvesting planners and machine operators by combining a GPS-driven application and a mobile app.
Murphy, P.N.C.; Ogilvie, J.; Arp, P. (2009): Topographic modelling of soil moisture conditions. A comparison and verification of two models. In: European Journal of Soil Science 60 (1), S. 94–109. DOI: 10.1111/j.1365-2389.2008.01094.x.
Murphy, P.N.C.; Ogilvie, Jae; Connor, Kevin; Arp, Paul (2007): Mapping wetlands: A comparison of two different approaches for New Brunswick, Canada. In: WETLANDS 27 (4), S. 846–854.
Murphy, Paul N.C.; Ogilvie, Jae; Meng, Fan-Rui; White, Barry; Bhatti, Jagtar S.; Arp, Paul A. (2011): Modelling and mapping topographic variations in forest soils at high resolution. A case study. In: Ecological Modelling 222 (14), S. 2314–2332. DOI: 10.1016/j.ecolmodel.2011.01.003.
Schönauer, Marian; Talbot, Bruce; Jaeger, Dirk (2019): TECH4EFFECT. Terrain accessibility maps for 4 case study areas.
White, Barry; Ogilvie, Jae; Campbell, David M.H. M.H.; Hiltz, Douglas; Gauthier, Brian; Chisholm, H. Kyle H. et al. (2012): Using the Cartographic Depth-to-Water Index to Locate Small Streams and Associated Wet Areas across Landscapes. In: Canadian Water Resources Journal 37 (4), S. 333–347. DOI: 10.4296/cwrj2011-909.
This project has received funding from the Bio Based Industries Joint Undertaking under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 720757.