For the northeastern US, the Anthropocene has been dominated by land use change from forestland to developed area, and in places, back to forested land (i.e. forest transition). The impacts of forest transition have long term effects on ecosystems health. In particular, understanding the loss of “core areas” is imperative, since core areas are generally not as vulnerable to invasion by exotic species and are more resilient to the effects of climate change. However, current methods of estimating core area are not particularly precise; since “edge” is quite variable. This study devises a new method for identifying edge depths along a transition between anthropogenic and forested landscapes using LiDAR. Eight transects, located perpendicular to the edge of an abandoned golf course at Harvard Forest, in Petersham, MA, were sampled. Vegetation inventories and Photosynthetically Active Radiation at different heights through the canopy were collected to define field edge depth for each transect. These measurements were then compared with small-footprint aerial LiDAR datasets to model edge depths. Simple canopy height profiles, created by binning the discrete LiDAR returns into height classes, were used to predict edge depth and checked for independence from the field derived edge depths.
All edge depths predicted using discrete return LiDAR data were within 5 meters of the field predicted edge depths and the two estimated edge depths were not significantly different (χ2 = 12.267, df = 7, p-value = 0.1987). Given that the sampling distance between locations along each transect was 5 meters, and possible geolocation errors from either the GPS (Trimble Nomad) or LiDAR returns, this finding indicates that the process of binning discrete aerial LiDAR returns to create canopy height profiles is an appropriate method for mapping edge depths when canopy structure is a good delimiter of edge and core habitats. In this particular location in the northeastern US, the most useful predictor of edge depth was the disappearance/reduction of plant matter in the 0.15-1 meter range and an increase in the 2-4 meter and > 4 meter range, as seen in both the field and LiDAR data. While this is a novel finding and useful in creating better estimates of remaining core forested area, further work should be pursued to determine the precise conditions under which discrete return LiDAR can be used to establish edge depths and the accuracy with which it can be done on a landscape scale.