A framework for a forest ecological base map-An example from Norway

In the management of forest ecosystems, spatial information about the extent, condition and pressures are essential. In the current study, we present a framework for a remote sensing-based forest ecological base map covering Norway. Combining remotely sensed imagery from optical satellite systems such as Sentinel-2 and Landsat provides information about forest ecosystem extent and change over time. Utilizing a national dataset of airborne laser scanning (ALS) data allowed predicting a range of attributes describing forest condition, including naturalness. In total, seven definitions of naturalness were evaluated. Pressures on the forest ecosystems were mapped using a change detection algorithm and satellite data from 1986 to 2020. Change detection is the cornerstone in monitoring and for understanding the pressures on the ecosystems. The predicted forest extent had an overall accuracy of 85 to 89% using Sentinel-2 imagery from 2020 and 71 to 81% using Landsat imagery from 1986. For the forest condition attributes, the explained portion of the variances were >70% for biomass, height and volume and from 21% to 64% for number of stems, crown coverage and a diversity index. Naturalness was classified with accuracies of 77 to 98%, except for age-based definitions. Nevertheless, a large number of false positives were present. Change detection was evaluated in terms of final harvest and was identified with an overall accuracy of 84-92%. The land cover change classification had an overall accuracy of 70-92%. The detailed maps of forest condition and forest pressures were aggregated to a local level using model-based inference, providing estimates of mean values and uncertainty at a scale suitable for ecosystem indicator development. The collection of map layers describing forest extent, condition and pressures form a forest ecological base map important for environmental management.

Automated summary

This study presents a framework for a remote sensing-based forest ecological base map in Norway, which provides spatial information about the extent, condition, and pressures of forest ecosystems. The framework combines optical satellite imagery with airborne laser scanning data to predict forest condition and map pressures on the ecosystems using change detection algorithms. The accuracy of the predicted forest extent and condition attributes is relatively high, and the maps are aggregated at a local level for ecosystem indicator development.