Characterizing the Spectral-Temporal Signatures of Eastern Hemlock (Tsuga Canadensis) Using Sentinel-2 Satellite Images and Phenology Modelling

Abstract

Hemlock woolly adelgid (HWA) is an invasive insect that affects the eastern hemlock population in North America, causing severe die-off and altering ecosystem dynamics. Understanding the distribution of eastern hemlock will improve future HWA management and protection of existing eastern hemlock populations. To determine the degree to which different forest types and species can be distinguished at the stand level with variable densities of eastern hemlock present, a Bayesian phenology model was used to compute seven phenological parameters from four spectral indices derived from Sentinel-2 time series imagery. We tested spectral and phenological parameters derived using this method across three classification levels, including broad forest type, hemlock density, and dominant or co-dominant evergreen species. Using Kruskal-Wallis with post-hoc Dunn’s test, we found that phenological parameters derived from the Inverted Red-Edge Chlorophyll Index and the Soil-Adjusted Vegetation Index provided the highest separability between groups across all three levels of classification. The seasonal minimum greenness and fall inflection day provided the highest degree of separability among hemlock density classes. Seasonal minimum greenness provided the highest degree of separability among evergreen species. Among the nine evergreen dominant or co-dominant species classes tested, hemlock stands were found to be separable from four of the classes. White pine stands and black spruce stands showed the highest degree of overall separability. This study demonstrates the potential for phenological parameters in stand-level evergreen species classification. The combination of Sentinel-2 time series and phenological modeling has the potential to enhance tree species mapping studies at regional scales.