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Object-Based Classification as an Alternative Approach to the Traditional Pixel-Based Classification to Identify Potential Habitat of the Grasshopper Sparrow

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Abstract

The traditional method of identifying wildlife habitat distribution over large regions consists of pixel-based classification of satellite images into a suite of habitat classes used to select suitable habitat patches. Object-based classification is a new method that can achieve the same objective based on the segmentation of spectral bands of the image creating homogeneous polygons with regard to spatial or spectral characteristics. The segmentation algorithm does not solely rely on the single pixel value, but also on shape, texture, and pixel spatial continuity. The object-based classification is a knowledge base process where an interpretation key is developed using ground control points and objects are assigned to specific classes according to threshold values of determined spectral and/or spatial attributes. We developed a model using the eCognition software to identify suitable habitats for the Grasshopper Sparrow, a rare and declining species found in southwestern Québec. The model was developed in a region with known breeding sites and applied on other images covering adjacent regions where potential breeding habitats may be present. We were successful in locating potential habitats in areas where dairy farming prevailed but failed in an adjacent region covered by a distinct Landsat scene and dominated by annual crops. We discuss the added value of this method, such as the possibility to use the contextual information associated to objects and the ability to eliminate unsuitable areas in the segmentation and land cover classification processes, as well as technical and logistical constraints. A series of recommendations on the use of this method and on conservation issues of Grasshopper Sparrow habitat is also provided.

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Acknowledgments

We thank Martine Benoit for her help with GIS work and data processing and Claudie Latendresse and Guillaume Tremblay for field assistance. Daniel St-Hilaire provided valuable information on the Grasshopper Sparrow’s historical and current distribution in the Pontiac region. We thank two anonymous reviewers for their valuable comments on the manuscript. Our sincere thanks also go to every landowner for granting us access to their property. Financial support was provided by the Canadian Wildlife Service, Québec Region, Environment Canada.

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  1. Canadian Wildlife Service, Environment Canada, 1141 route de l’Église, C.P. 10100, Sainte-Foy, G1V 4H5, Québec, Canada

    Benoît Jobin, Sandra Labrecque, Marcelle Grenier & Gilles Falardeau

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  1. Benoît Jobin
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Correspondence to Benoît Jobin.

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Jobin, B., Labrecque, S., Grenier, M. et al. Object-Based Classification as an Alternative Approach to the Traditional Pixel-Based Classification to Identify Potential Habitat of the Grasshopper Sparrow. Environmental Management 41, 20–31 (2008). https://doi.org/10.1007/s00267-007-9031-0

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