DOI: 10.1016/j.foreco.2017.05.017
Scopus记录号: 2-s2.0-85019904440
论文题名: Mapping post-disturbance forest landscape composition with Landsat satellite imagery
作者: Savage S.L. ; Lawrence R.L. ; Squires J.R.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2017
卷: 399 起始页码: 9
结束页码: 23
语种: 英语
英文关键词: Biotic legacy
; Disturbance ecology
; Forest landscape composition
; Landsat satellite imagery
; Percent canopy cover
; Spruce beetle
Scopus关键词: Climate change
; Ecology
; Forecasting
; Image processing
; Managers
; Mapping
; Reforestation
; Satellite imagery
; Satellites
; Biotic legacy
; Canopy cover
; Disturbance ecology
; Forest landscape
; Landsat satellite
; Spruce beetles
; Forestry
; biotic factor
; canopy architecture
; climate change
; community composition
; environmental disturbance
; forest ecosystem
; forest management
; global climate
; image processing
; Landsat
; mortality
; parasite infestation
; regeneration
; satellite imagery
; survival
; vegetation mapping
; Colorado
; Rio Grande National Forest
; United States
; Dendroctonus rufipennis
英文摘要: Forests worldwide are impacted by a wide variety of disturbances that are happening more frequently with more intensity than in the past due to global climate change. Forest managers, therefore, need to identify new ways to quickly and accurately predict post-disturbance forest landscape composition. We suggest the use of Landsat satellite imagery and an image processing tool to map percent canopy cover (PCC) by species and sub-canopy species counts to be used in adaptive forest management strategies. We used zero-inflated models to successfully predict PCC and sub-canopy counts (number of regenerating trees per pixel, also called biotic legacies) for 4 tree species, along with overall PCC and percent mortality, for a large portion of the Rio Grande National Forest (RGNF) in 2013. The RGNF had recently been disturbed by spruce beetle (Dendroctonus rufipennis) infestation since the early 2000s and the West Fork Fire Complex in 2013. Our PCC models resulted in pseudo median differences between observed and predicted values of 0.2–6.5%, RMSE of 10.9–17.0%, and 95% confidence interval widths of 4.4–24.9%, depending on the species. The percent mortality model resulted in pseudo median differences between observed and predicted values of 1.1%, RMSE of 12.4%, and 95% confidence interval width of 4.6%. The sub-canopy PCC model resulted in a pseudo median differences between observed and predicted values of 1.3%, RMSE of 9.4%, and 95% confidence interval of 3.0%. The sub-canopy count models resulted in mean differences of 0.1–1.4 trees, RMSE of 3.0–13.4 trees, and 95% confidence interval widths of 1.1–5.0 trees, depending on species. By mapping PCC and sub-canopy counts, we have provided forest managers with knowledge of the current surviving forest (PCC) as well as the biotic legacies (sub-canopy counts) that can aid in forming hypotheses as to what the forest might become in the future, adding to the forest manager toolbox for forest management strategies. The methods described can be applied to a variety of issues within the field of disturbance ecology and, combined with change analyses, will provide forest managers with empirical evidence of current and future forest composition along with biological legacies that will impact forest regeneration. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/64268
Appears in Collections: 影响、适应和脆弱性
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作者单位: Department of Land Resources & Environmental Sciences, Montana State University, PO Box 173120, Bozeman, MT, United States; Rocky Mountain Research Station, USDA Forest Service, 800 E. Beckwith, Missoula, MT, United States
Recommended Citation:
Savage S.L.,Lawrence R.L.,Squires J.R.. Mapping post-disturbance forest landscape composition with Landsat satellite imagery[J]. Forest Ecology and Management,2017-01-01,399