Earth observation (EO) capabilities to produce up-to-date geographical information on slums
over large areas supporting urban planning and evidence-based policymaking are largely …

The lack of sufficient ground truth data has always constrained supervised learning, thereby
hindering the generation of up-to-date satellite-derived thematic maps. This is all the more …

Research on spatial non-stationarity of land-cover classification accuracy has been ongoing
for over two decades with most of the work focusing on single date maps. We extend the …

Detailed information on the spatial-temporal change of impervious surfaces is important for
quantifying the effects of rapid urbanization. Free access of the Landsat archive provides …

With the unprecedented availability of satellite data and the rise of global binary maps, the
collection of shared reference data sets should be fostered to allow systematic product …

Ground reference data are typically required to evaluate the quality of a supervised image
classification analysis used to produce a thematic map from remotely sensed data. Acquiring …

Rapid growth in the field of quantitative digital image analysis is paving the way for scientific
researchers to make precise measurements about objects in an image. To compute …

Massive and high-quality in situ data are essential for Earth-observation-based agricultural
monitoring. However, field surveying requires considerable organizational effort and money …

Reference data collected to validate land-cover maps are generally considered free of
errors. In practice, however, they contain errors despite best efforts to minimize them. These …

Land cover maps contribute to a large diversity of geospatial applications, including but not
limited to land management, hydrology, land use planning, climate modeling and …