Uncertainty propagation in the model web: a case study with e-Habitat

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Abstract

eHabitat is a Web Processing Service (WPS) designed to compute the likelihood of finding ecosystems with equal properties. Inputs to the WPS, typically thematic geospatial "layers", can be discovered using standardised catalogues, and the outputs tailored to specific end user needs. Because these layers can range from geophysical data captured through remote sensing to socio-economical indicators, eHabitat is exposed to a broad range of different types and levels of uncertainties. Potentially chained to other services to perform ecological forecasting, for example, eHabitat would be an additional component further propagating uncertainties from a potentially long chain of model services. This integration of complex resources increases the challenges in dealing with uncertainty. For such a system, as envisaged by initiatives such as the "Model Web" from the Group on Earth Observations, to be used for policy or decision making, users must be provided with information on the quality of the outputs since all system components will be subject to uncertainty. UncertWeb will create the Uncertainty-Enabled Model Web by promoting interoperability between data and models with quantified uncertainty, building on existing open, international standards. It is the objective of this paper to illustrate a few key ideas behind UncertWeb using eHabitat to discuss the main types of uncertainties the WPS has to deal with and to present the benefits of the use of the UncertWeb framework.

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Publication date1 Dec 2011
Publication title34th International Symposium on Remote Sensing of Environment - The GEOSS Era: Towards Operational Environmental Monitoring
PublisherICRSE
Original languageEnglish
Event34th International Symposium on Remote Sensing of Environment - Sydney, NSW, Australia

Symposium

Symposium34th International Symposium on Remote Sensing of Environment
CountryAustralia
CitySydney, NSW
Period10/04/1115/04/11
OtherThe GEOSS Era: Towards Operational Environmental Monitoring

    Keywords

  • ecological forecasting, model web, SOA, uncertainties, web processing services

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