  The accuracy assessment of remote-sensing derived built-up land data
represents a specific case of binary map comparison, where class imbalance
varies considerably across rural-urban trajectories. Thus, local accuracy
characterization of such datasets requires specific strategies that are robust
to low sample sizes and different levels of class imbalance. Herein, we examine
the suitability of commonly used spatial agreement measures for their localized
accuracy characterization of built-up land layers across the rural-urban
continuum, using the Global Human Settlement Layer and a reference database of
built-up land derived from cadastral and building footprint data.
