Object Based Change Detection of Historical Aerial Photographs Reveals Altitudinal Forest Expansion

Object based image classification is applied to assess the upward advance of tree species in Finnish Lapland caused by the current global warming. An automated Feature Extraction Module (Fx) implemented in ENVI is used to extract the tree crowns from a digitized panchromatic aerial photograph acquired in 1947 and a false colour aerial photograph from 2003 of an altitudinal foresttundra ecotone on Lommoltunturi fell (a mountain shaped by Pleistocene glaciations). The two step Fx process included segmentation and feature classification with support vector machines with textural, spatial and spectral channels as inputs. The change in the resulted relative crown areas of Norway spruce (Picea abies) and downy birch (Betula pubenscens) were then assessed in GIS analysis, and compared to forest inventory and age data of saplings and trees. Within the last 56 years, Norway spruce has expanded uphill, in terms of distance, approximately 100 m and birch 40 to 60 m. In accordance with the birch-pine-spruce succession concept, the downy birch dominated forest-tundra ecotone stands are now replaced by Norway spruce. The treeline of Scots pine (Pinus sylvestris) reach the fell top (557 m a.sl.). The spruce and birch treelines reach 510 m. We did not find water availability, soil temperature nor N to be limiting factors in expansion of spruce-birch forest but a surplus of Al relative to base cations may disfavour spruce on some sites in the tundra. Primarily, the harsh winter wind-climate and spatial variability in thickness of snow cover are presently restricting the regeneration of trees on the open tundra.