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The purpose of this paper is to contribute to the definition of a European perspective on Digital Earth (DE), identify some actions that can contribute to raise the awareness of DE in the European context and thus strengthen the European contribution to the International Society for Digital Earth (ISDE). The paper identifies opportunities and synergies with the current policy priorities in Europe (Europe 2020, Innovation Union and Digital Agenda) and highlights a number of key areas to advance the development of DE from a European perspective: (1) integrating scientific research into DE; (2) exploiting the Observation Web with human-centred sensing; and (3) governance, including the establishment of stronger linkages across the European landscape of funding streams and initiatives. The paper is offered also as a contribution to the development of this new vision of DE to be presented at the next International DE Conference in Perth, Australia, in August 2011. The global recognition of this new vision will then reinforce the European component and build a positive feedback loop for the further implementation of DE across the globe. [ABSTRACT FROM AUTHOR]

Cloud computing facilities can provide crucial computing support for processing the time series of satellite data and exploiting their spatio-temporal information content. However, dedicated efforts are still required to develop workflows, executable on cloud-based platforms, for ingesting the satellite data, performing the targeted processes, and generating the desired products. In this study, an operational workflow is proposed, based on monthly Evaporative Stress Index (ESI) anomaly, and implemented in cloud-based online Virtual Earth Laboratory (VLab) platform, as a demonstration, to monitor European agricultural water stress. To this end, daily time-series of actual and reference evapotranspiration (ETa and ET0), from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor, were used to execute the proposed workflow successfully on VLab. The execution of the workflow resulted in obtaining one decade (2011–2020) of European monthly agricultural water stress maps at 0.04˚ spatial resolution and corresponding stress reports for each country. To support open science, all the workflow outputs are stored in GeoServer, documented in GeoNetwork, and made available through MapStore. This enables creating a dashboard for better visualization of the results for end-users. The results from this study demonstrate the capability of VLab platform for water stress detection from time series of SEVIRI-ET data. [ABSTRACT FROM AUTHOR]

Mapping geographic concentrations of quaternary industries (QIs) may help to assess regional performance and formulate informed development policies. However, fine resolution data on QIs concentrations are sparsely reported. Thus, for the year 2010, only 45% of all NUTS3 regions (i.e. regions of the third and most detailed level of the Nomenclature of Units for Territorial Statistics of the EU) provide relevant information. In this study, we investigate a possibility that artificial light-at-night (ALAN), captured by satellite sensors, can help to identify geographic concentrations of QIs. In this study, we use year-2010 NUTS3 Eurostat data, and combine them with data on ALAN intensities, obtained from the U.S. Defense Meteorological Satellite Program (US-DMSP) for the years 2000 and 2010. In both ordinary least squares (OLS) and spatial dependency (SD) models, ALAN emerged as a statistically significant predictor (t = 8.392-14.608; P < .01), helping to explain, along with other predictors, up to 75% of QIs regional variation. The obtained models and regional data presently available enabled estimates of QIs concentrations for European NUTS3 regions with missing data. [ABSTRACT FROM AUTHOR]