Digital Earth (DE) is a powerful metaphor for the organisation and access to digital information through a multi-scale three-dimensional representation of the globe. Recent progress gave a concrete body to this vision. However, this body is not yet self-aware: further integration of the temporal and voluntary dimension is needed to better portray the event-based nature of our world. We thus aim to extend DE vision with a Nervous System in order to provide decision makers with improved alerting mechanisms. Practical applications are foreseen for crisis management, where up-to-date situational awareness is needed. While it is traditionally built through trusted sources, citizens can play a complementary role by providing geo-referenced information known as Volunteered Geographic Information (VGI). Although workflows have been implemented to create, validate and distribute VGI datasets for various thematic domains, its exploitation in real time and its integration into existing concepts of DE, such as spatial data infrastructures, still needs to be further addressed. In this paper we suggest to bridge this gap through Sensor Web Enablement for VGI, where VGI sensing becomes a sense of the DE's Nervous System. We discuss this approach and its applicability in the context of a forest fire scenario.

, Como, Italy. The authors were invited to submit an extended version to this special issue. Apart from editorial changes, we included a new section on the sensing of multiple VGI platforms and an extensive discussion section on generalizing the approach towards a nervous system for the next generation of geospatial information infrastructures (Digital Earth). Pointers to related works have been extended, too.Abstract. There is a long tradition of non specialists contributing to the collection of geo-referenced information. Thanks to recent convergence of greater access to broadband connections, the availability of Global Positioning Systems in small packages at affordable prices, and more participative forms of interaction on the Web (Web 2.0) vast numbers of individuals became able to create and share Volunteered Geographic Information (VGI). The potential of up to 6 billion persons to monitor the state of the environment, validate global models with local knowledge, contribute to crisis situations awareness, and provide information that only humans can capture is vast and has yet to be fully exploited. Integrating VGI into Spatial Data Infrastructures (SDI) is a major challenge, as it is often regarded as insufficiently structured, documented or validated according to scientific standards. Early instances of SDIs used to have limited ability to manage and process geosensor-based data (beyond remotely sensed imagery snapshots), which tend to arrive in continuous streams of real-time information. The current works on standards for Sensor Web Enablement (SWE) aim to fill this gap. This paper shows how such standards can be applied to VGI, thus converting it in a timely, cost-effective and valuable source of information for SDIs. By doing so, we extend previous efforts describing a workflow for VGI integration into SDI and further advance an initial set of VGI Sensing and event detection techniques. Examples of how such VGI Sensing techniques can support crisis information system are provided. The presented approach serves central building blocks for a Digital Earth's nervous system, which is required to develop the next generation of (geospatial) information infrastructures.

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The emergence of innovative web applications, often labelled as Web 2.0, has permitted an unprecedented increase of content created by non-specialist users. In particular, Location-based Social Networks (LBSN) are designed as platforms allowing the creation, storage and retrieval of vast amounts of georeferenced and user-generated contents. LBSN can thus be seen by Geographic Information specialists as a timely and cost-effective source of spatio-temporal information for many fields of application, provided that they can set up workflows to retrieve, validate and organise such information. This paper aims to improve the understanding on how LBSN can be used as a reliable source of spatio-temporal information, by analysing the temporal, spatial and social dynamics of Twitter activity during a major forest fire event in the South of France in July 2009.

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