Integration of Environmental Models in Spatial Data Infrastructures: A Use Case in Wildfire Risk Prediction
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Other documents of the author: Trilles, Sergio; Juan, Pablo; Díaz, Laura; Aragó Galindo, Pau; Huerta, Joaquin
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comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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Title
Integration of Environmental Models in Spatial Data Infrastructures: A Use Case in Wildfire Risk PredictionDate
2013Publisher
Institute of Electrical and Electronics Engineers (IEEE)ISSN
1939-1404Bibliographic citation
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, VOL. 6, NO. 1, FEBRUARY 2013Type
info:eu-repo/semantics/articlePublisher version
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6415305Version
info:eu-repo/semantics/acceptedVersionSubject
Abstract
Achieving sustainable growth in our society implies
monitoring our environment in order to measure human impact
and detect relevant changes and detrimental driving factors such
as wildfires and desertification. In ... [+]
Achieving sustainable growth in our society implies
monitoring our environment in order to measure human impact
and detect relevant changes and detrimental driving factors such
as wildfires and desertification. In order for experts to perform
environmental modelling they need to be able to access data and
models in an efficient and interoperable manner as well as share
their findings to assist other professionals in decision making. In
the current information society, distributed information systems
are essential for sharing digital resources such as data and tools.
Advances in Service-Oriented Architectures (SOA) allow for the
distribution and accessibility of on-line resources such as data and
tools, which served through standards-based services improve the
sharing of data, models and models results.
This research presents a service-oriented application that
addresses the issues of interoperable access to environmental
modelling capabilities as well as the mechanisms to share their
results an efficiently throughout interoperable components. The
aim is twofold, first we present different models for multi-scale
forest fire risk prediction based on spatial point processes, and
second we provide this functionality as a distributed application,
that, based on international standards, such as those offered by
the Open Geospatial Consortium (OGC), improves interoperable
access to these models as well as the publication of the results to
be shared with other interested stakeholders. [-]
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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, vol. 6, no 1Rights
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