GSTDTAP  > 气候变化
DOI10.1016/j.foreco.2017.05.021
Characterizing historical fire patterns as a guide for harvesting planning using landscape metrics derived from long term satellite imagery
San-Miguel, Ignacio1; Andison, David W.2; Coops, Nicholas C.1
2017-09-01
发表期刊FOREST ECOLOGY AND MANAGEMENT
ISSN0378-1127
EISSN1872-7042
出版年2017
卷号399
文章类型Article
语种英语
国家Canada
英文摘要

Forest managers across the Canadian boreal require detailed fire pattern information to support disturbance-based management. However, there are no consistent classifications of post-fire patterns, and those that exist rely on field-data that is both expensive and lacking in spatial representation. As a result, across the managed boreal forest there is limited fire pattern information, no standardized protocols to derive the quantitative fire pattern information nor agreement on the most appropriate metrics needed to implement management planning based on emulating natural disturbances. In this paper we first derived three classes of tree mortality based on Landsat spectral data and aerially photo interpreted (API) polygons. Next we used these derived classes to compute seven fire pattern metrics over 14 fires that occurred from 1984 to 2006 in the Canadian provinces of Alberta and Saskatchewan, Canada. We then compared the metrics derived from the Landsat data to those computed from the API coverage. Lastly, we assessed the influence of a suite of environmental and fire pattern variables on the Landsat-derived indices. Overall we found very close correspondence for the two event-scale indices: the total area affected by fire and the complexity of the perimeter. The more detailed within-fire event metrics presented more varied results and were somewhat less precise. For example, the total amount of residuals or the largest disturbed patch were accurately captured. Other indices such as the number of disturbed patches or total amount of island remnants presented moderate systematic biases, but still might be serviceable given that the biases were predictable in direction. Fire size and seasonal drought variables were the most correlated with the Landsat derived pattern indices and their inclusion as model variables is likely to increase overall prediction accuracy. A pan-boreal geospatial database of detailed fire pattern metrics would be an invaluable tool to support the implementation of disturbance-based management approaches. Here we demonstrate that a cost-effective Landsat methods produces comparable fire pattern information to conventional approaches based on manual interpretation of aerial photographs. Building upon the standardized methods proposed here hundreds of fires could be mapped, to potentially, create a comprehensive national fire pattern database. (C) 2017 Elsevier B.V. All rights reserved.


英文关键词Harvesting Fire emulation Historical range of variability Patch metrics Fire patterns Landsat sensor
领域气候变化
收录类别SCI-E
WOS记录号WOS:000404195800015
WOS关键词BOREAL FOREST ; BURN SEVERITY ; WILDFIRE ; CANADA ; CLASSIFICATION ; MANAGEMENT ; MORTALITY ; DYNAMICS ; DNBR
WOS类目Forestry
WOS研究方向Forestry
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/22638
专题气候变化
作者单位1.Univ British Columbia, Dept Forest Resources Management, Integrated Remote Sensing Studio, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada;
2.Bandaloop Landscape Ecosyst Serv, 1011 Hendecourt Rd, N Vancouver, BC V7K 2X3, Canada
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GB/T 7714
San-Miguel, Ignacio,Andison, David W.,Coops, Nicholas C.. Characterizing historical fire patterns as a guide for harvesting planning using landscape metrics derived from long term satellite imagery[J]. FOREST ECOLOGY AND MANAGEMENT,2017,399.
APA San-Miguel, Ignacio,Andison, David W.,&Coops, Nicholas C..(2017).Characterizing historical fire patterns as a guide for harvesting planning using landscape metrics derived from long term satellite imagery.FOREST ECOLOGY AND MANAGEMENT,399.
MLA San-Miguel, Ignacio,et al."Characterizing historical fire patterns as a guide for harvesting planning using landscape metrics derived from long term satellite imagery".FOREST ECOLOGY AND MANAGEMENT 399(2017).
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