Characterizing Tree Species in Northern Boreal Forests Using Multiple-Endmember Spectral Mixture Analysis and Multi-Temporal Satellite Imagery ...

• Main Authors: Van der Sluijs, Jurjen, Peddle, Derek R., Hall, Ronald J.
• Format: Text
• Language: unknown
• Published: Taylor & Francis 2023
• Subjects: Space Science; Environmental Sciences not elsewhere classified; Ecology; FOS Biological sciences; Biological Sciences not elsewhere classified; Plant Biology; Canada; Northwest Territories
• Online Access: https://dx.doi.org/10.6084/m9.figshare.23274583.v1; https://tandf.figshare.com/articles/journal_contribution/Characterizing_Tree_Species_in_Northern_Boreal_Forests_Using_Multiple-Endmember_Spectral_Mixture_Analysis_and_Multi-Temporal_Satellite_Imagery/23274583/1

Northern boreal forests are characterized by open stands whereby trees, understory background, and shadow are all significant components of the spectral response within a pixels’ spatial footprint. To overcome this mixed pixel problem, accurate spectral characterization of these (endmember) components is necessary for spectral mixture analysis (SMA) to generate forest classifications at the species level. Obtaining these endmember spectra in the field, however, can be difficult or impossible. This study examined whether image endmember spectra can be identified using forest inventory information to derive dominant tree species classifications. This was tested using multiple-endmember SMA (MESMA) and single- and multi-date Landsat imagery of a forested area in the Northwest Territories, Canada. Image classifications ( n = 80) were generated based on 20 image-date combinations and four unmixing models. Accuracies of 80% and 82% were achieved for open and medium dense forest stands, respectively using ...