Image classification is a complex process that may be affected by many factors. This paper
examines current practices, problems, and prospects of image classification. The emphasis …

The remote sensing community has identified data fusion as one of the key challenging
topics of the 21st century. The subject of image fusion in two-dimensional (2D) space has …

Clear presentation of uncertainty is an exception rather than rule in media articles, data-
driven reports, and consumer applications, despite proposed techniques for communicating …

Developing reliable methods for representing and managing information uncertainty
remains a persistent and relevant challenge to GIScience. Information uncertainty is an …

Many visual depictions of probability distributions, such as error bars, are difficult for users to
accurately interpret. We present and study an alternative representation, Hypothetical …

Natural hazard models are vital for all phases of risk assessment and disaster management.
However, the high number of uncertainties inherent to these models is highly challenging for …

Abstract Digital Elevation Models (DEMs) such as Advanced Spaceborne Thermal Emission
and Reflection Radiometer Global Digital Elevation Models (ASTER GDEM), or Shuttle …

Flood inundation mapping is a critical task for responding to the increasing risk of flooding
linked to global warming. Significant advancements of deep learning in recent years have …

Quantification of rainfall and its spatial and temporal variability is extremely important for
reliable hydrological and meteorological modeling. While rain gauge measurements do not …

Geospatial datasets of forest characteristics are modeled representations of real populations
on the ground. The continuous spatial character of such datasets provides an incredible …