Multilayer Architecture for Heterogeneous Geospatial Data Analytics: Querying and Understanding EO Archives

The constantly growing process of the Earth Observation (EO) data and their heterogeneity require new systems and tools for effectively querying and understanding the available data archives. In this paper, we present a tool for heterogeneous geospatial data analytics. The system implements different web technologies in a multilayer server–client architecture, allowing the user to visually analyze satellite images, maps, and in-situ information. Specifically, the information managed is composed of EO multispectral and synthetic aperture radar products along with the multitemporal in-situ LUCAS surveys. The integration of these data provides a very useful information during the EO scene interpretation process. The system also offers interactive tools for the detection of optimal datasets for EO multitemporal image change detection, providing at the same time ground-truth points for both human and machine analyses. Furthermore, we show by means of visual analytic representations a way to analyze and understand the content and distribution of the EO databases.