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TitleDigital photograph analysis for measuring percent plant cover in the Arctic
AuthorChen, Z; Chen, W; Leblanc, S G; Henry, G H R
SourceArctic vol. 63, no. 3, 2010 p. 315-326
Alt SeriesEarth Sciences Sector, Contribution Series 20090265
Mediapaper; on-line; digital
File formatpdf
NTS25N/15; 27F/08
AreaIqaluit; Clyde River
Lat/Long WENS -68.5500 -68.5167 63.7833 63.7500
Lat/Long WENS -68.4833 -68.4833 70.5000 70.4667
Subjectsgeophysics; remote sensing; satellite imagery; vegetation; climate, arctic; ecosystems
Illustrationssatellite images; plots; tables
ProgramClimate Change Impacts and Adaptation for Key Economic and Natural Environment Sectors, Climate Change Geoscience
AbstractLong-term satellite remote sensing data, when properly calibrated and validated against ground monitoring, could provide valuable data sets for assessing climate change impacts on ecosystems, wildlife, and other important aspects of life in the Arctic. Percent plant cover is ideal for seasonal and long-term ground monitoring because it can be observed non-destructively and is closely related to other key ecosystem variables, such as biomass and leaf area index (LAI). Accurately measuring percent plant cover in the Arctic, however, has been a challenge. Advances in digital photography and imageprocessing techniques have provided the potential to measure vegetation cover accurately. In this paper we report an adapted method for quantifying percent plant cover based on plot digital photograph classification (PDPC). In this digital image analysis, the red, green, and blue image channels and the intensity, hue, and saturation image channels were used together to ensure more accurate cover measurement and labeling of plant species. We evaluated the accuracy of the PDPC method and two other techniques, visual estimate and digital grid overlay, by testing against artificial plots with known percent cover, by comparing with destructively measured LAI, and by comparing results of the three methods. Our evaluation indicates that the PDPC method is the most accurate. In addition, PDPC has the advantages of being objective, quick in the field, and suitable for measuring percent plant cover in the Arctic at the level of functional types or species groups.