Canadian Forest Service Publications

Influence of field-based species composition and understory descriptions on spectral mixture analysis of tree species in the Northwest Territories, Canada. 2016. Van der sluijs, J.; Hall, R.J.; Peddle, D.R. Canadian Journal of Remote Sensing 42(5):591-609.

Year: 2016

Issued by: Northern Forestry Centre

Catalog ID: 37174

Language: English

Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.1080/07038992.2016.1196581

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Tree species information is a fundamental component of forest inventories that is challenging to obtain in northern boreal forests because inherently open stands with individual trees might be clumped or widely distributed and contain multiple tree species. These challenges result in a mixed pixel problem that was investigated using Multiple Endmember Spectral Mixture Analysis (MESMA), a technique for identifying the type and proportions of forest components (e.g., sunlit canopy, background vegetation, shadow) in remotely sensed imagery at the subpixel scale. This was tested using Landsat Thematic Mapper (TM) imagery from a study area in the Northwest Territories (NWT), Canada. How the dominant tree species was described in the field, and how the spectral properties of understory vegetation was measured, were both important factors that affected species discrimination. Landsat TM was most sensitive to dominant species defined by the fraction of total basal area of the dominant and codominant trees. Classification accuracies of 90% and 63% for very open and medium density forest stands, respectively, were achieved when understory diversity and abundance information was incorporated into the definition of the background component. It was concluded that this approach warrants further investigation for northern boreal forest species classification.

Plain Language Summary

Collecting information about forest species is a fundamental component of a forest inventory. The vast forests in the Northwest Territories are largely inaccessible making the collection of this information a challenging proposition. To help resolve this problem, of interest was how well forest species could be interpreted and mapped from remote sensing (the acquisition and analysis of data from satellites). Relevant questions to this problem was whether how forest species is described in the field, and whether detailed knowledge of understory vegetation would influence the analysis of the remote sensing image. By comparing four field-based descriptions of forest species, the most accurate remote sensing-based map was from a description based on its order of dominance in the forest canopy. The knowledge of understory vegetation also proved to be an important discriminating factor to mapping forest species. The study provides the foundation for determining how satellite remote sensing could be used to map forest species composition in a northern boreal forest environment.