DOI: 10.1016/j.jag.2013.11.013
Scopus记录号: 2-s2.0-84897559654
论文题名: Quantification of anthropogenic and natural changes in oil sands mining infrastructure land based on RapidEye and SPOT5
作者: Zhang Y ; , Guindon B ; , Lantz N ; , Shipman T ; , Chao D ; , Raymond D
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 29, 期: 1 起始页码: 31
结束页码: 43
语种: 英语
英文关键词: Change detection
; Extraction of land changes
; Land disturbance
; Mining land
; Reclamation
; Regrowth
Scopus关键词: accuracy assessment
; anthropogenic effect
; bitumen
; detection method
; disturbance
; human activity
; land use change
; oil sand
; pixel
; quantitative analysis
; reclaimed land
; satellite data
; SPOT
; Alberta
; Canada
; Fort McMurray
英文摘要: Natural resources development, spanning exploration, production and transportation activities, alters local land surface at various spatial scales. Quantification of these anthropogenic changes, both permanent and reversible, is needed for compliance assessment and for development of effective sustainable management strategies. Multi-spectral high resolution imagery data from SPOT5 and RapidEye were used for extraction and quantification of the anthropogenic and natural changes for a case study of Alberta bitumen (oil sands) mining located in the Western Boreal Plains near Fort McMurray, Canada. Two test sites representative of the major Alberta bitumen production extraction processes, open pit and in situ extraction, were selected. A hybrid change detection approach, combining pixel- and object-based target detection and extraction, is proposed based on Change Vector Analysis (CVA). The extraction results indicate that the changed infrastructure landscapes of these two sites have different footprints linked with their differing oil sands production processes. Pixel- and object-based accuracy assessments have been applied for validation of the change detection results. For manmade disturbances, except for those fine linear features such as the seismic lines, accuracies of about 80% have been achieved at the pixel level while, at the object level, these rise to 90-95%. Since many disturbance features are transient, a new landscape index, entitled the Re-growth Index, has been formulated at single object level specifically to monitor restoration of these features to their natural state. It is found that the temporal behaviour of the Re-growth Index in an individual patch varies depending on the type of natural land cover. In addition, the Re-growth Index is also useful for assessing the detectability of disturbed sites. © 2014 Published by Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79677
Appears in Collections: 气候变化事实与影响
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作者单位: Canada Centre for Remote Sensing, Earth Sciences Sector, Natural Resources Canada, 588 Booth Street, Ottawa, ON K1A 0Y7, Canada; Alberta Geological Survey, Alberta Energy Regulator, 4999-98 Avenue, Edmonton, AB T6B 2X3, Canada
Recommended Citation:
Zhang Y,, Guindon B,, Lantz N,et al. Quantification of anthropogenic and natural changes in oil sands mining infrastructure land based on RapidEye and SPOT5[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,29(1)