Abstract
This chapter introduces a novel ensemble learning framework called spatial ensemble, which is used to classify heterogeneous spatial data with class ambiguity. Class ambiguity refers to the phenomenon whereby samples with similar features belong to different classes at different locations (e.g., spectral confusion between different thematic classes in earth observation imagery). This chapter also provides preliminary results of comparison between spatial ensemble and traditional ensemble learning (e.g., bagging, boosting, and random forest) on wetland mapping datasets.
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Jiang, Z., Shekhar, S. (2017). Spatial Ensemble Learning. In: Spatial Big Data Science. Springer, Cham. https://doi.org/10.1007/978-3-319-60195-3_6
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DOI: https://doi.org/10.1007/978-3-319-60195-3_6
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