Research Papers

Narrow-linear and small-area forest disturbance detection and mapping from high spatial resolution imagery

[+] Author Affiliations
Yuhong He

University of Toronto Mississauga, Department of Geography, 3359 Mississauga North Road, Mississauga, ON L5L1C6 Canada

Steven E. Franklin

Trent University, 1600 West Bank Drive, Peterborough, ON K9J7B8 Canada

Xuling Guo

University of Saskatchewan, Department of Geography and Planning, 117 Science Place, Saskatoon, Saskatchewan S7N 5C8 Canada

Gordon B. Stenhouse

Alberta Sustainable Resource Development, Fish and Wildlife Division, Box 6330, Hinton, AB T7V 1X6 Canada

J. Appl. Remote Sens. 3(1), 033570 (December 11, 2009). doi:10.1117/1.3283905
History: Received June 5, 2009; Revised November 16, 2009; Accepted December 7, 2009; December 11, 2009; Online December 11, 2009
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Abstract

Widespread disturbance has brought a large amount of narrow-linear and small-area disturbance features (e.g., trails, seismic lines, forest roads, well sites, and cut blocks) to forest areas throughout the past decade. This issue has prompted research into finding the appropriate data and methods for mapping these narrow-linear and small-area disturbance features in order to examine their impacts on wildlife habitat. In this paper, we first described the characteristics of small forest disturbances and presented the nature of problem. We then presented a framework for detecting and extracting narrow-linear and small-area forest disturbance features. Using a SPOT 5 high spatial detail image and existing GIS databases, we applied the framework to map narrow-linear and small-area forest disturbance features in a Bear Management area (BMA) in the eastern slopes of the Rocky Mountains in Alberta, Canada. The results indicated that the proposed framework produced accurate disturbance maps for cut blocks, and forest roads & trails. The high errors of omission in the cut lines map were attributed to inconsistent geometric and radiometric patterns in the 'rarely-used' or 'old' cut lines. The study confirmed the feasibility of rapidly updating incomplete GIS data with linear and small-area disturbance features extracted from high spatial detail SPOT imagery. Future work will be directed towards improvement of the framework and the extraction strategy to remove a large amount of spurious features and to increase accuracy for cut lines mapping.

© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

Yuhong He ; Steven E. Franklin ; Xuling Guo and Gordon B. Stenhouse
"Narrow-linear and small-area forest disturbance detection and mapping from high spatial resolution imagery", J. Appl. Remote Sens. 3(1), 033570 (December 11, 2009). ; http://dx.doi.org/10.1117/1.3283905


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