A hybrid approach to mapping vernal pools in Rhode Island using photointerpretation guided by LiDAR

Mapping potential vernal pools (PVPs) through remote sensing is important for guiding the management of these key habitats. Photointerpretation of PVPs from springtime aerial imagery is time consuming and prone to errors of omission (e.g. from obscuration by coniferous trees) and commission (e.g. from tree shadows). We tested a hybrid mapping approach that uses LiDAR- and image-based geospatial indicators to guide photointerpretation of PVPs. We created 5 indicators, based on established and novel approaches, to detect characteristics of PVPs. These characteristics included depressions in the elevation model, voids in ground-level LiDAR returns, low intensity of ground-level LiDAR returns, and very low brightness in 4-band (RGB, NIR) multispectral imagery. The hybrid approach had omission and commission errors of 14% and 19%, respectively, for aquatic depressions. A photointerpretation-only approach (for a different study area) had omission and commission errors of 10% and 32%, respectively. Subjectively, we found the hybrid approach to be more efficient compared to the photointerpretation-only approach. PVPs associated with more than 2 indicators had very low commission errors (< 4%) which suggests that co-occurring indicators can be used identify PVPs that are more likely to be actual vernal pools. The hybrid approach combined the ability of LiDAR and imagery to detect vernal pool characteristics with the ability of a human photo-interpreter to reduce commission errors.