Comparing object-based and pixel-based classifications for mapping savannas

By Timothy G. Whiteside, Guy S. Boggs, Stefan W. Maier. International Journal of Applied Earth Observation and Geoinformation, 2011

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Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data (2012, background): “This is true in particular, if the pixel size is significantly smaller than the average size of the objects of interest [34–36].”
Geographic Object-Based Image Analysis – Towards a new paradigm (2014, result): “…articles that have shown that object-based classiﬁcation results (especially of H-resolution imagery) are consistently better than those based on traditional pixel-based approaches (e.g., Shackelford and Davis, 2003; Yu et al, 2006; Blaschke, 2010; Myint et al., 2011; Whiteside et al., 2011).”
Land Use/Land Cover Change Analysis Using Object-Based Classification Approach in Munessa-Shashemene Landscape of the Ethiopian Highlands (2013, methodology): “Recently, object-based image analysis has been applied more frequently for remote sensing image classification than pixel-based analysis [35,36].”
Modelling of land-use change in Thailand using binary logistic regression and multinomial logistic regression (2020, background): “The problem of a few studies on the statistical applications on land-use is as a result of some limitations on the structure of land-used data (Whiteside et al. 2011).”