Finding the right pixel size

By Tomislav Hengl. Computational Geosciences, 2006

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A Practical Guide to Geostatistical Mapping (2009, background): “Both concepts are closely related with cartographic scale (Hengl, 2006).”
Evaluation of UAV imagery for mapping Silybum marianum weed patches (2017, background): “As a generic rule, at least four pixels per object (weed or weed patch) have been suggested as the optimum resolution in weed mapping (Hengl 2006; López-Granados 2011).”
Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling (2015, methodology): “All maps used in this paper were tessellated with a pixel size of 100 m × 100 m (cf. Carranza, 2009; Hengl, 2006; Zuo, 2012)”
Airborne LiDAR for DEM generation: some critical issues (2008, background): “…grid size is dependent on source data density (McCullagh, 1988; Hu, 2003), terrain complexity (Gao, 1997; Chou et al., 1999; Hengl et al., 2003; Hengl, 2006), and applications (Barber and Shortrudge, 2004; Kienzle, 2004; Ziadat, 2007). any surface so generated is more likely to represent the…”
Tree Species Classification in Boreal Forests With Hyperspectral Data (2013, methodology): “In order to map the spatial objects under analysis properly, Hengl in [39] suggested having at least four pixels representing the smallest objects and at least two pixels representing the narrowest objects.”