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Estimating the Height and Basal Area at Individual Tree and Plot Levels in Canadian Subarctic Lichen Woodlands Using Stereo WorldView-3 Images

Geography Department, Université du Québec à Montréal, Montréal, QC H3C 3P8, Canada
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Remote Sens. 2019, 11(3), 248; https://doi.org/10.3390/rs11030248
Received: 12 December 2018 / Revised: 21 January 2019 / Accepted: 22 January 2019 / Published: 26 January 2019
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Abstract

Lichen woodlands (LW) are sparse forests that cover extensive areas in remote subarctic regions where warming due to climate change is fastest. They are difficult to study in situ or with airborne remote sensing due to their remoteness. We have tested a method for measuring individual tree heights and predicting basal area at tree and plot levels using WorldView-3 stereo images. Manual stereo measurements of tree heights were performed on short trees (2–12 m) of a LW region of Canada with a residual standard error of ≈0.9 m compared to accurate field or UAV height data. The number of detected trees significantly underestimated field counts, especially in peatlands in which the visual contrast between trees and ground cover was low. The heights measured from the WorldView-3 images were used to predict the basal area at individual tree level and summed up at plot level. In the best conditions (high contrast between trees and ground cover), the relationship to field basal area had a R2 of 0.79. Accurate estimates of above ground biomass should therefore also be possible. This method could be used to calibrate an extensive remote sensing approach without in-situ measurements, e.g., by linking precise structural data to ICESAT-2 footprints. View Full-Text
Keywords: high resolution; spaceborne; photogrammetry; taiga; black spruce; stem density; unmanned aerial vehicles high resolution; spaceborne; photogrammetry; taiga; black spruce; stem density; unmanned aerial vehicles
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St-Onge, B.; Grandin, S. Estimating the Height and Basal Area at Individual Tree and Plot Levels in Canadian Subarctic Lichen Woodlands Using Stereo WorldView-3 Images. Remote Sens. 2019, 11, 248.

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