Quantification of changes in oil sands mining infrastructure land based on RapidEye and SPOT5

Ying Zhang; Nicholas Lantz; Bert Guindon; Todd Shipman; Dennis Chao; Don Raymond

doi:10.1117/12.2029001

24 October 2013 Quantification of changes in oil sands mining infrastructure land based on RapidEye and SPOT5

Ying Zhang, Nicholas Lantz, Bert Guindon, Todd Shipman, Dennis Chao, Don Raymond

Proceedings Volume 8893, Earth Resources and Environmental Remote Sensing/GIS Applications IV; 889302 (2013) https://doi.org/10.1117/12.2029001
Event: SPIE Remote Sensing, 2013, Dresden, Germany

Abstract

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 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. Pixeland object-based accuracy assessments have been applied for validation of the change detection results. For manmade disturbances, other than 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, the land surface changes by re-growth of vegetation and the capability for natural restoration on the mining sites have been assessed.

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Ying Zhang, Nicholas Lantz, Bert Guindon, Todd Shipman, Dennis Chao, and Don Raymond "Quantification of changes in oil sands mining infrastructure land based on RapidEye and SPOT5", Proc. SPIE 8893, Earth Resources and Environmental Remote Sensing/GIS Applications IV, 889302 (24 October 2013); https://doi.org/10.1117/12.2029001

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KEYWORDS

Mining

Image segmentation

Image resolution

Sensors

Vegetation

Roads

Satellites

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