Self-supervised representation learning (SSRL) concerns the problem of learning a useful
data representation without the requirement for labelled or annotated data. This …

The aim of this article is to provide a basis in evidence for (or against) the much-quoted
assertion that 80% of all information is geospatially referenced. For this purpose, two …

Geospatial analysis is crucial for addressing many of the world's most pressing challenges.
Given this, there is immense value in improving and expanding the visualization techniques …

Over the past decade, rapid advances in web technologies, coupled with innovative models
of spatial data collection and consumption, have generated a robust growth in geo …

Global urbanization and the growing need for sustainable transportation solutions are
increasing the demand for electric vehicle (EV) infrastructure. This research aims to identify …

This paper proposes an interoperable model for managing high dimensional point clouds
while integrating semantics. Point clouds from sensors are a direct source of information …

The importance of knowledge organization and information retrieval techniques has been
evident throughout human history, becoming even more crucial in the digital age. While …

Agro-geoinformatics deals with collecting, managing, and analyzing agricultural-related
geospatial data, which are domain-specific big data. This chapter discusses the general …

Data is spatial if it contains references to space. We can easily detect explicit references, for
example coordinates, but we cannot detect whether data implicitly contains references to …

Information is called spatial if it contains references to space. The thesis aims at lifting the
characterization of spatial information to a structural level. Tobler's first law of geography and …