Can Landsat imagery detect tree line dynamics?

Prior research on tree line dynamics has primarily been based on field inventory data, and little is known about the potential for using remotely sensed imagery to detect change. The present study developed a new methodology by combining remote sensing and field survey data to examine dynamics of the pristine forest in the tree line area on Changbai Mountain in Northeast China over the past two decades. The new method normalized remote sensing data by using the adjacent old‐growth coniferous forest (close to climax) below the tree line as the reference (assuming steady state) to eliminate various potential errors associated with different satellite sensors, atmospheric conditions and seasonal vegetation changes. Specifically, we used a ratio of normalised difference vegetation index (NDVI) between the tree line forest (birch) and the referenced old‐growth coniferous forest, as well as a ratio between the interface forest against the referenced coniferous forest, to investigate growth dynamics of the tree line forest from 1977 to 1999. The interface forest is distributed between the tree line forest and non‐forest zone. Compared with traditional methods using remote sensing data, the new method has higher sensitivity to tree line dynamics. We found that the tree line delineated from satellite imagery had shown no shift in the past decades. However, the NDVI ratio of tree line forest against the reference forest increased from 0.9 to 1.2 from 1977 to 1999, and the ratio of interface forest against the reference forest increased from 0.83 to 0.98, indicating that growth of the tree line forest apparently exceeded that of the reference coniferous forest and had grown denser. Field surveys also supported the conclusion from remote sensing results that the tree line forest on Changbai Mountain has grown denser in the past decades. From 1980 to 2002, basal area of the tree line forest increased 35% (from 18.8 to 25.3 m2 ha−1); at the same time the NDVI ratio increased about 33%. This study suggests that it is possible to monitor growth of the tree line forest based on multi‐temporal remote sensing images. We speculate that global warming may have contributed to the observed rapid growth of the tree line forest because temperature is a major limiting factor among climatic variables in the tree line forest and effect from other factors, such as fire, harvesting and snow and wind damage, were not evident in this protected area in the past decades.