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Open AccessArticle

Differentiation of Alternate Harvesting Practices Using Annual Time Series of Landsat Data

Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5, Canada
Author to whom correspondence should be addressed.
Academic Editors: Christian Ginzler and Lars T. Waser
Forests 2017, 8(1), 15;
Received: 2 December 2016 / Revised: 22 December 2016 / Accepted: 23 December 2016 / Published: 28 December 2016
(This article belongs to the Special Issue Optimizing Forest Inventories with Remote Sensing Techniques)
Sustainable forest management practices allow for a range of harvest prescriptions, including clearcut, clearcut with residual, and partial or selective cutting, which are largely distinguished by the amount of canopy cover removed. The different prescriptions are aimed to emulate natural disturbance, encourage regeneration (seed trees), or offer other ecosystem services, such as the maintenance of local biodiversity or habitat features. Using remotely sensed data, stand-replacing disturbance associated with clearcutting is commonly accurately detected. Novel time series-based change detection products offer an opportunity to determine the capacity to detect and label a wider range of harvest practices. In this research, we demonstrate the capacity of time series imagery, spectral metrics, and related attributed change products, to distinguish between different harvesting practices over a study area in central British Columbia, Canada. Producer’s accuracy of harvest attribution was 79%, with 93% of harvest blocks >5 ha accurately identified. In relation to the amount of canopy cover removed, clearcut harvesting was the most accurately classified (84%), followed by clearcut with residual (79%), and partial cut (64%). Applying detailed spectral metrics derived from Landsat data revealed clearcut and partial cuts to be spectrally distinct. The annual nature of the Landsat time series also offers spatial harvest information within typical, often decadal, forest inventory update cycles. The statistically significant (p < 0.05) relationship between harvest practices and Landsat spectral information indicates a capacity to add increased attribution richness to remote sensing depictions of forest harvest. View Full-Text
Keywords: harvesting; remote sensing; disturbance analysis; Landsat; time series harvesting; remote sensing; disturbance analysis; Landsat; time series
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Jarron, L.R.; Hermosilla, T.; Coops, N.C.; Wulder, M.A.; White, J.C.; Hobart, G.W.; Leckie, D.G. Differentiation of Alternate Harvesting Practices Using Annual Time Series of Landsat Data. Forests 2017, 8, 15.

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