Repository CRAN

Description Package for geostatistical interpolation of data with irregular spatial support such as runoff related data or data from administrative units

eHabitat: Large scale modelling of habitats types and similarities for conservation and management of protected areas.

eHabitat, which is one of the services supporting the DOPA, the Digital Observatory for Protected Areas, proposes a habitat replaceability index (HRI) which can be used for characterizing each protected area worldwide. More precisely, eHabitat computes for each protected area a map of probabilities to find areas within the corresponding ecoregion presenting ecological characteristics that are similar to those found in the selected protected area. The HRI is then computed as the ratio between similar areas outside park and the park area itself. We here present an improved version which includes an automatic segmentation of the parks prior to HRI computation. This allows for a discrimination of different habitats types inside of protected areas. By reducing the variability within landscape patches, similarity values can be considered to be more accurate. This approach should also further improve the associated niche modelling tools.JRC.H.5-Land Resources Managemen

Uncertainty propagation in the Model Web: A case study with e-Habitat

e-Habitat 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, e-Habitat is exposed to a broad range of different types and levels of uncertainties. Potentially chained to other services to perform ecological forecasting for example, e-Habitat 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 Group on Earth Observation¿s ¿Model Web¿, 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. UncertWeb will thus develop open source implementations of encoding standards, service interface profiles, discovery and chaining mechanisms, and generic tools to realize a "Model Web" taking uncertainty in data and models into account. It is the objective of this paper to discuss the main types of uncertainties e-Habitat has to deal with and to present the benefits of the use of the UncertWeb framework.JRC.H.3-Global environement monitorin

eHabitat: A Contribution to the Model Web for Habitat Assessments and Ecological Forecasting

In striving to improve the predictive capabilities of ecological forecasting we face three basic choices ¿ develop new models, improve existing ones or increase the connectivity of models so they can work together. The latter approach of chaining different interoperable models is of particular interest, as technical developments have made it increasingly viable to combine models that can answer more questions than the individual models alone, allowing users to address complex questions, often of a multi-disciplinary nature. This concept of a Model Web encourages the setting up of a dynamic network of interoperating models, communicating with each other using standardized web services. It is the purpose of this paper to introduce the potential contribution of e-Habitat to the Model Web. e-Habitat is conceived as a Web Processing Service for computing the likelihood of finding ecosystems with equal properties. By developing e-Habitat according to Model Web principles, end-users can define the thematic layers for input to the model from various sources. These input layers are discovered using standards-based catalogues, which are a fundamental component of Model Web and generic Spatial Data Infrastructures. e-Habitat integrates data ranging from remote sensing data to socio-economical indicators, thus offering a huge potential for multi-disciplinary modelling. We will show that e-Habitat can be used for the identification of habitats that are most vulnerable or of the optimal locations for monitoring stations or, when coupled with climate change model services, for ecological forecasting. As such, it is an excellent example of the Model Web in practice.JRC.H.3-Global environement monitorin

An introduction to the Digital Observatory for Protected Areas (DOPA) and the DOPA Explorer (Beta)

The Digital Observatory for Protected Areas (DOPA) is conceived around a set of interacting Critical Biodiversity Informatics Infrastructures (databases, web modelling services, broadcasting services, ...) hosted at different institutions, including the Joint Research Centre of the European Commission, the World Conservation Monitoring Centre (UNEP-WCMC), the International Union for Conservation of Nature (IUCN), the Global Biodiversity Information Facility (GBIF) and BirdLife International. The current services of DOPA provide to a large variety of end-users, ranging from park managers, funding agencies to researchers, with means to assess, monitor and possibly forecast the state and pressure of protected areas at the local, national and global scales. With an introduction to the DOPA, the readers will find here a user manual of the beta version of DOPA Explorer, a first web based assessment tool where information on 9 000 protected areas covering almost 90% of the global protected surface has been processed automatically to generate a set of indicators on ecosystems, climate, phenology, species, ecosystem services and pressures. DOPA Explorer can so help identify the protected areas with most unique ecosystems and species and assess the pressures they are exposed to because of human development. Ecological data derived from and near real-time earth observations are also made available for the African continent. Inversely, DOPA Explorer indirectly highlights the protected areas for which the information is incomplete.JRC.H.5-Land Resources Managemen

Assessment of the capacity for flood monitoring and early warning in Enlargement and Eastern/ Southern Neighbourhood countries of the European Union

Flooding is a natural disaster that can damage large areas in the vicinity of rivers, and in the case of flash floods, also in the vicinity of smaller streams. The Global Risks Report 2017 lists extreme weather events, of which flooding is the main risk in most countries, as the risk with the second highest potential impact and the highest likelihood of occurrence. It furthermore seems likely that climate change will aggravate flood impacts in many regions. This report presents an assessment of the capacity for flood monitoring and early flood warning in 17 of the 22 countries which belong to the Eastern and Southern neighbourhood policy of the European Union and the enlargement candidate countries. Many of these receive external funding to improve their systems, but this is often on an ad hoc basis and through individual projects.JRC.E.1-Disaster Risk Managemen

EFAS upgrade for the extended model domain

This publication is a Technical report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication.JRC.E.1-Disaster Risk Managemen

EFAS upgrade for the extended model domain

This publication is a Technical report by the Joint Research Centre (JRC), the European Commission’s science and knowledge service. It aims to provide evidence-based scientific support to the European policymaking process. The scientific output expressed does not imply a policy position of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use that might be made of this publication.JRC.E.1-Disaster Risk Managemen