Comparison of two algorithms for estimating stand-level changes and change indicators in a boreal forest in Norway

Abstract

In Europe, the change in forest cover caused by felling activities, especially clear-cutting, is the most significant driver of forest ecosystem change. Monitoring the magnitude of harvest activities and their spatial and temporal distribution can provide essential change indicators of the pressure on forest ecosystems. Satellite remote sensing offers the means to assess and map indicators of forest change dynamics related to a high spatial- and temporal resolution over large areas cost-effectively and objectively. Large-scale maps of forest cover change over time produced by LandTrendr (LT), a temporal segmentation algorithm, and Global Forest Watch (GFW) are evaluated in a Norwegian boreal environment. Their accuracy to detect change at stand-level and their potential to produce landscape-level spatial and temporal change indicators was assessed against a 20-year historical record of harvest activities in Southern Norway. Data from LT were found to be spatially and temporally more coherent with the reference data than GFW. LT detected 85.4% of the clear-cuts and a decrease in harvest activities between 2001 and 2017, a trend confirmed by the reference data, while GFW detected 63.1% of the clear-cuts and an increase in harvest activities for the same period. It was concluded that LT map of changes (LT-map) provides efficient spatial and temporal indicators of forest change dynamics and performed better than GFW tree cover loss map (GFW-map) to identify and monitor clear-cuts in a Norwegian boreal forest.

Keywords

• Clear-cut detection
• LandTrendr
• Large-scale mapping
• Landsat
• Global Forest Watch
• Change indicators