Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2, 179-185, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2/179/2014/
doi:10.5194/isprsarchives-XL-2-179-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 Nov 2014
Mapping forest stand complexity for woodland caribou habitat assessment using multispectral airborne imagery
W. Zhang1, B. Hu1, and M. Woods2 1Department of Earth and Space Science and Engineering, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada
2Forested Landscape, Ontario Ministry of Natural Resources, 3301 Trout Lake Road, North Bay, ON P1A 3J7, Canada
Keywords: Stand complexity, wildlife habitat, vertical structure, texture analysis, VHR imagery Abstract. The decline of the woodland caribou population is a result of their habitat loss. To conserve the habitat of the woodland caribou and protect it from extinction, it is critical to accurately characterize and monitor its habitat. Conventionally, products derived from low to medium spatial resolution remote sensing data, such as land cover classification and vegetation indices are used for wildlife habitat assessment. These products fail to provide information on the structure complexities of forest canopies which reflect important characteristics of caribou’s habitats. Recent studies have employed the LiDAR system (Light Detection And Ranging) to directly retrieve the three dimensional forest attributes. Although promising results have been achieved, the acquisition cost of LiDAR data is very high. In this study, utilizing the very high spatial resolution imagery in characterizing the structural development the of forest canopies was exploited. A stand based image texture analysis was performed to predict forest succession stages. The results were demonstrated to be consistent with those derived from LiDAR data.
Conference paper (PDF, 1019 KB)


Citation: Zhang, W., Hu, B., and Woods, M.: Mapping forest stand complexity for woodland caribou habitat assessment using multispectral airborne imagery, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2, 179-185, doi:10.5194/isprsarchives-XL-2-179-2014, 2014.

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