GIS and Data Layers Support Sustainable Forest Management in North Rhine-Westphalia

To sustainably manage Germany’s North Rhine-Westphalia (NRW), forest owners and administrators use ArcGIS to study forest conditions and surrounding infrastructure. GIS helps them identify areas that are most suitable for industrial timber production and make informed decisions for sustainable forest management.

NRW has approximately 900,000 hectares of private and municipal forestland next to a high-density population (18 million people). To support the region’s forestland owners, Landesbetrieb Wald und Holz NRW (LWH) provides comprehensive maps about the conditions and infrastructure related to forestry property. The staff uses GIS to describe its forest management recommendations.

LWH analysts designed a model for visualizing the resource utilization potential of forests. The model gives forest owners an overview of four important aspects of their forest lands: operating limitations for harvesting and transportation equipment, physical soil stability, resource development, and biomass productivity. LWH maintains a forestry database from which it creates different types of maps available for the whole federal state of NRW. Here are descriptions of these maps using the example of National Park Eifel:

Forest Resource Development map—GIS reveals forest areas that are accessible to logging trucks and harvesting equipment throughout the year. The ArcGIS Spatial Analyst extension was used to calculate cost distance and optimum travel corridors. Moreover, it factored in travel obstacles within the road network to generate a true cost evaluation. This map is a combination of two data layers: a wooded area timber inventory and forestland locations that are accessible for hauling logs in all seasons.



Slope Classes for Trafficability map—Forestry machines such as feller bunchers, harvesters, skidders, forwarders, and loaders can operate only on specific terrains. The steeper the forest, the less likely that machines can operate safely. Analysts used GIS to examine a gridded digital elevation model (DEM) of the area and create the map. Three classes were differentiated as follows:



Physical Stability map—Bulk density is a measure of the weight of soil per unit volume, which is used to describe the porosity and moisture retention of the soil. Analysts created a soil stability map that shows the values of bulk density and soil types. GIS makes it easy to see on this map areas that have similar soil makeup characteristics. For the purposes of this analysis, soil types are classified as the following:



Potential Biomass Productivity map—This map contains hydrologic requirements of forest vegetation from climatologic data and water datasets derived from the soil map. This is essential for high timber yields.


Each of these GIS-generated maps helps LWH convey forest information in an easyto-understand way, thereby improving forest managers’ decisions. Data layers for individual forest maps were combined to create a comprehensive map (page 8). LWH added analysis to the map classes by assigning priority ratings according to importance and significance levels.

GIS then incorporated these priorities into the maps. The map output from this model is the resource utilization potential of forests, which shows area-to-timber priority levels along with jurisdictional boundaries and rivers.



The North Rhine-Westphalia utilization map prioritizes areas for timber productivity. This map makes it easy for responsible forest owners to quickly understand land-use options for a range of timber production priorities.


For more information, contact the authors: Frank Franken, Hessen-Forst FENA, Gießen, Germany (e-mail: frank.franken@forst.hessen.de), or Dr. Stefan Franz, Landesbetrieb Wald und Holz NRW, Münster, Germany (e-mail: stefan.franz@wald-und-holz.nrw.de).

ESRI Forestry GIS Journal, Spring 2010
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