The physical phenomena derived from an analysis of remotely sensed imagery provide a
clearer understanding of the spectral variations of a large number of land use and cover …

Geospatial big data plays a major role in the era of big data, as most data today are
inherently spatial, collected with ubiquitous location-aware sensors such as mobile apps …

Multi-dimensional arrays (also known as raster data or gridded data) play a key role in
many, if not all science and engineering domains where they typically represent spatio …

In this paper, we present ForeCache, a general-purpose tool for exploratory browsing of
large datasets. ForeCache utilizes a client-server architecture, where the user interacts with …

SciDB: A Database Management System for Applications with Complex Analytics Page 1 54 This
arTicle has been peer-reviewed. COMPUTING IN SCIENCE & ENGINEERING S CIENCE D ATA …

With the advancement of GPS and remote sensing technologies, large amounts of
geospatial data are being collected from various domains, driving the need for effective and …

This paper introduces HadoopViz; a MapReduce-based framework for visualizing big spatial
data. HadoopViz has three unique features that distinguish it from other techniques.(1) It …

This paper introduces the open-source Beast system for scalable exploratory data science
on big spatio-temporal data. Beast is based on well-established research and has been …

Accurate and reliable forestry data can be obtained by means of continuous monitoring of
forests using advanced technologies, which provides a major opportunity for the …

The recent explosion in the amount of spatial data calls for specialized systems to handle
big spatial data. In this paper, we discuss the main features and components that needs to …