The Sentinel-Ready Multisensor Evolution Analysis System
Natali, Stefano; Mantovani, Simone; Barboni, Damiano; Veratelli, Maria Grazia
MEEO SRL, ITALY
The Automatic, Semantic Image Information Mining from Time Series of HR/VHR Images (ASIM) ESA Project aims at providing a web application (Multi-sensor Evolution Analysis - MEA) able to manage long time series of satellite-retrieved products such as land and sea surface temperatures, ocean salinity.
The system, through an easy-to-use web application permits to browse the loaded data, visualize their temporal evolution on a specific point with the creation of 2D graphs of a single field, or compare different fields on the same point (e.g. temperatures from different satellite products), and visualize maps of specific fields superimposed with high resolution background maps. All data access operations and display are performed by means of OGC standard operations namely WMS, WCS and WCPS.
The datasets available though the MEA system are ENVISAT-Related products, such as the entire MERIS MGVI and AATSR NDVI datasets, AATSR SST and LST (2002 - 2012), MODIS LST and cloud masks (2001 - 2012), Soil Moisture / Salinity form SMOS (since 2010) and WACMOS data (1979 - 2010). The geographic coverage ranges from European data up to global data.
Moreover, the system has been developed to be able to directly ingest Sentinel data once they are available, having the Military Grid Reference System (MGRS) as native CRS. Thus Level 1 and Level 2 Sentinel-derived datasets will be directly ingested by the system once available.
In the framework of this work, the system architecture, and the system functionalities in the real time exploitation of long time series of multi-sensor datasets with present data and perspectives with Sentinel data are presented and discussed.