DOI: 10.1016/j.jag.2014.06.015
Scopus记录号: 2-s2.0-84911365176
论文题名: Remote sensing and object-based techniques for mapping fine-scale industrial disturbances
作者: Powers R ; P ; , Hermosilla T ; , Coops N ; C ; , Chen G
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 34, 期: 1 起始页码: 51
结束页码: 57
语种: 英语
英文关键词: (GEOBIA)
; Boreal
; Disturbance
; Feature extraction
; Geographic object-based image analysis
; Oil sands
Scopus关键词: Boreal
; boreal forest
; environmental disturbance
; image analysis
; land classification
; mapping
; oil sand
; remote sensing
; satellite imagery
; spatial resolution
; SPOT
; Alberta
; Canada
英文摘要: Remote sensing provides an important data source for the detection and monitoring of disturbances; however, using this data to recognize fine-spatial resolution industrial disturbances dispersed across extensive areas presents unique challenges (e.g., accurate delineation and identification) and deserves further investigation. In this study, we present and assess a geographic object-based image analysis (GEO-BIA) approach with high-spatial resolution imagery (SPOT 5) to map industrial disturbances using the oilsands region of Alberta's northeastern boreal forest as a case study. Key components of this study were(i) the development of additional spectral, texture, and geometrical descriptors for characterizing image-objects (groups of alike pixels) and their contextual properties, and (ii) the introduction of decision trees with boosting to perform the object-based land cover classification. Results indicate that the approach achieved an overall accuracy of 88%, and that all descriptor groups provided relevant information for the classification. Despite challenges remaining (e.g., distinguishing between spectrally similar classes,or placing discrete boundaries), the approach was able to effectively delineate and classify fine-spatial resolution industrial disturbances. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79509
Appears in Collections: 气候变化事实与影响
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作者单位: Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC, Canada; Department of Geography and Earth Sciences, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, NC, United States
Recommended Citation:
Powers R,P,, Hermosilla T,et al. Remote sensing and object-based techniques for mapping fine-scale industrial disturbances[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,34(1)