@article{TrillesOliver2013,
title = {Integration of Environmental Models in Spatial Data Infrastructures: A Use Case in Wildfire Risk Prediction},
author = { Sergio Trilles-Oliver and Pablo Juan-Verdoy and Laura Diaz-Sánchez and Pau Aragó-Galindo and Joaquín Huerta-Guijarro},
url = {http://hdl.handle.net/10234/88029},
doi = {10.1109/JSTARS.2012.2236538},
issn = {1939-1404},
year = {2013},
date = {2013-01-01},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
volume = {6},
number = {1},
pages = {128--138},
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 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.},
note = {IF: 2.827, Q1},
keywords = {Environmental models, EUROGEOSS, forest fire, GEOCLOUD, RIESGOS-MEDIOAMBIENTALES, Spatial Data Infrastructures (SDI)},
pubstate = {published},
tppubtype = {article}
}

@article{DiazSanchez2013,
title = {Publishing sensor observations into Geospatial Information Infrastructures: A use case in fire danger assessment},
author = { Laura Díaz-Sánchez and Arne Bröring and Daniel McInerney and Giorgio Libertá and Theodor Foerster},
url = {http://hdl.handle.net/10234/159894},
doi = {10.1016/j.envsoft.2013.06.002},
issn = {13648152},
year = {2013},
date = {2013-01-01},
journal = {Environmental Modelling and Software},
volume = {48},
pages = {65-80},
publisher = {Elsevier Ltd},
abstract = {To improve environmental monitoring, the availability of large coverage, interoperable spatio-temporal data is crucial for its integration into environmental models, for example, to compute fire danger models. In order to produce up-to-date and accurate results, these models require data with high temporal and spatial resolution. Thus, it is promising to consider the increasing number of in-situ sensors providing observations of our environment in real-time. Today, interoperable access to such spatio-temporal data is achieved by Geospatial Information Infrastructures (GIIs). From a technical point of view, GIIs provide these data through standards-based Web service interfaces. While those Web service interfaces already enable the interoperable discovery and retrieval of sensor observations, the functionality to publish sensor observations is still an arduous task. Hence, in this paper, we present an approach to improve the registration of sensors and the publication of their observations via standards-based Web service interfaces. We evaluate our approach by extending a standards-based GII and by applying the developed approach as a proof of concept to integrate in-situ weather observations into the European Forest Fire Information System for assessing fire danger in Spain.},
note = {IF: 4.538, q1},
keywords = {Environmental models, EUROGEOSS, forest fire, Geospatial Information Infrastructures, OGC, Sensors, Spatial data infrastructures (SDI)},
pubstate = {published},
tppubtype = {article}
}

@article{McInerney2012,
title = {Developing a Forest Data Portal to Support Multi-Scale Decision Making},
author = { Daniel McInerney and Lucy Bastin and Laura Díaz-Sánchez and Carlos Figueiredo and José I. Barredo and Jesús San-Miguel-Ayanz},
url = {http://hdl.handle.net/10234/73426},
doi = {10.1109/JSTARS.2012.2194136},
issn = {1939-1404},
year = {2012},
date = {2012-12-01},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
volume = {5},
number = {6},
pages = {1692-1699},
abstract = {Forests play a pivotal role in timber production, maintenance and development of biodiversity and in carbon sequestration and storage in the context of theKyoto Protocol. Policy makers and forest experts therefore require reliable information on forest extent, type and change for management, planning and modeling purposes. It is becoming increasingly clear that such forest information is frequently inconsistent and unharmonised between countries and continents. This paper presents a forest information portal that has been developed in line with the GEOSS and INSPIRE frameworks. The web portal provides access to forest resource data at a variety of spatial scales, from global through to regional and local, as well as providing analytical capabilities for monitoring and validating forest change. The system also allows for the utilisation of forest data and processing services within other thematic areas. The web portal has been developed using open standards to facilitate accessibility, interoperability and data transfer.},
note = {IF: 2.874, Q1},
keywords = {earth observation, EUROGEOSS, forest fire},
pubstate = {published},
tppubtype = {article}
}

@article{TrillesOliver2012b,
title = {Integración de modelos medioambientales en infraestructuras de datos espaciales: un caso de uso en predicción de incendios},
author = {Sergio Trilles-Oliver and Pablo Juan-Verdoy and Laura Díaz-Sánchez},
url = {http://repositori.uji.es/xmlui/bitstream/handle/10234/159887/Trilles_Juan_Diaz_Huerta_RCG_44_2012.pdf?sequence=1},
issn = {1988-2459},
year = {2012},
date = {2012-01-01},
journal = {Revista catalana de geografía},
volume = {XVII},
number = {44},
keywords = {Environmental models, forest fire, geoprocessing, Spatial Data Infrastructures (SDI)},
pubstate = {published},
tppubtype = {article}
}