eHabitat, a multi-purpose Web Processing Service for ecological modeling

The number of interoperable research infrastructures has increased significantly with the growing awareness of the efforts made by the Global Earth Observation System of Systems (GEOSS). One of the Societal Benefit Areas (SBA) that is benefiting most from GEOSS is biodiversity, given the costs of monitoring the environment and managing complex information, from space observations to species records including their genetic characteristics. But GEOSS goes beyond simple data sharing to encourage the publishing and combination of models, an approach which can ease the handling of complex multi-disciplinary questions. It is the purpose of this paper to illustrate these concepts by presenting eHabitat, a basic Web Processing Service (WPS) for computing the likelihood of finding ecosystems with equal properties to those specified by a user. When chained with other services providing data on climate change, eHabitat can be used for ecological forecasting and becomes a useful tool for decision-makers assessing different strategies when selecting new areas to protect. eHabitat can use virtually any kind of thematic data that can be considered as useful when defining ecosystems and their future persistence under different climatic or development scenarios. The paper will present the architecture and illustrate the concepts through case studies which forecast the impact of climate change on protected areas or on the ecological niche of an African bird

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

Real-Time Water Decision Support Services For Droughts

Through application of computational methods and an integrated information system, real-time data and river modeling systems can help decision makers identify more effective actions for management practice. The purpose of this study is to develop a real-time decision support model to recommend optimal curtailments during water shortages for decision makers. To enable ease of use and re-use, the workflows (i.e., analysis and model steps) of the real-time decision support model are published as Web services delivered through an internet browser, including model inputs, a published workflow service, and visualized outputs. The model consists of two major components: the real-time river flow prediction system and the optimization model. The RAPID model, which is a river routing model developed at University of Texas Austin for parallel computation of river discharge, is applied to predict real-time river flow rates. The workflow of the RAPID model has been built and published as a Web application that allows non-technical users to remotely execute the model and visualize results as a service through a simple Web interface. An optimization model is being developed to provide real-time water withdrawal decision support using the RAPID output and the clustering particle swarm optimization algorithm (CPSO) and genetic algorithm methods. The model is being tested using historical drought data from 2011 in the Upper Guadalupe River Basin in Texas. The objective of the optimization is to assist the Texas Commission on Environmental Quality (TCEQ) in minimizing the total daily curtailment hours of all permit holders, with constraints on user seniority and ecological river flow. The optimization model workflows is linked to the RAPID model workflow to provide real-time water decision support services. Finally, visualization of the output using Bing-map and WorldWide Telescope helps decision makers predict outcomes from alternative weather or policy scenarios

EXPOSING AND PROVIDING ACCESS TO INDIAN BIORESOURCE INFORMATION NETWORK (IBIN) SPECIES OCCURRENCE DATASET AS WEB SERVICE USING OGC WPS STANDARD

Species occurrence data are collected by many researchers worldwide as record of species present at a specific time at some defined place as part of biological field investigation serving as primary or secondary dataset. These datasets reside in separate silos across numerous distributed systems having different formats limiting its usage to full potential. IBIN portal provides a single window for accessing myriad spatial/non-spatial data on bioresources of the country. To promote reuse of occurrence dataset among organizations in an interoperable format including support for integration across various platforms & programming languages, it is been exposed as web service using OGC Web Processing Service (WPS) standard. WPS provides standardized interface for performing online geo-processing by exposing spatial processes, algorithms and calculations thereby enabling machine to machine communication and wider usage in various scenarios (e.g. service chaining etc.). Open source ZOO-project is used for developing the ‘Species Search’ WPS service. WPS takes inputs as either the species name or bounding box or shapefile defining the area of interest and returns queryable OGC complaint Web Map Service (WMS) as output with specie(s) occurrences represented in grid (5km x 5km) format, with each grid possessing attributes like specie(s) name, family, state, medicinal detail etc. WPS process can be invoked asynchronously, enabling proper feedback regarding status of the job submitted. JavaScript based web client for consuming this service has also been developed along with custom QGIS plugin to allow potential users to access the same in GIS software for wider reusability

Image time series processing for agriculture monitoring

AbstractGiven strong year-to-year variability, increasing competition for natural resources, and climate change impacts on agriculture, monitoring global crop and natural vegetation conditions is highly relevant, particularly in food insecure areas. Data from remote sensing image series at high temporal and low spatial resolution can help to assist in this monitoring as they provide key information in near-real time over large areas. The SPIRITS software, presented in this paper, is a stand-alone toolbox developed for environmental monitoring, particularly to produce clear and evidence-based information for crop production analysts and decision makers. It includes a large number of tools with the main aim of extracting vegetation indicators from image time series, estimating the potential impact of anomalies on crop production and sharing this information with different audiences. SPIRITS offers an integrated and flexible analysis environment with a user-friendly graphical interface, which allows sequential tasking and a high level of automation of processing chains. It is freely distributed for non-commercial use and extensively documented

Assessing habitat diversity and potential areas of similarity across protected areas globally

Biophysical characterization analyses of protected areas (PA) that provide information on their ecological values and potential areas with similar characteristics are needed to make informed PA network planning and management decisions. This study combines and further develops methodologies that use remote sensing and modelling to identify habitat functional types in PAs and map similar areas at the ecoregion level. The study also develops new terrestrial habitat diversity and irreplaceability indices at habitat and PA scale that allow the comparison and ranking of PAs in terms of biophysical gradients and singular environmental conditions. Six PAs were selected to highlight and discuss the results of the proposed methodology. Both individual and composite indices should be considered when trying to compare PAs to understand the overall complexity and ecological values of each PA. Results can inform planning and management of individual and protected area networks as well as identify new areas for conservation. The information provided by the model about similar habitats outside protected areas can also help assess their representativeness and support studies to strengthen ecological connectivity. Besides systematic comparisons, detailed assessments of protected areas can also be performed using medium and high-resolution input variables. This is especially relevant for protected areas in developing countries where undertaking fieldwork is very difficult and the budget devoted to conservation is limited.European Commission European Commission Joint Research CentreBiodi- versity and Protected Areas Management (BIOPAMA) programme, an initiative of the African, Caribbean and Pacific (ACP) Group of StatesMarie Curie Actions CT-EX2020D381533-101Spanish Ministry of Universities and Next Generation European Union fund

From global observations to local information: The Earth Observation Monitor

Earth Observation (EO) data are available around the globe and can be used for a range of applications. To support scientists and local stakeholders in the usage of information from space, barriers, especially in data processing, need to be reduced. To meet this need, the software framework Earth Observation Monitor provides access and analysis tools for global EO vegetation time-series data based on standard-compliant geo-processing services. Data are automatically downloaded from several data providers, processed, and time-series analysis tools for vegetation analyses extract further information. A web portal and a mobile application have been developed to show the usage of interoperable geospatial web services and to simplify the access and analysis of global EO time-series data. All steps from data download to analysis are automated and provided as operational geo-processing services. Open-source software has been used to develop the services and client applications

The Digital Observatory for Protected Areas (DOPA) Explorer 1.0

The Digital Observatory for Protected Areas (DOPA) has been developed to support the European Union’s efforts in strengthening our capacity to mobilize and use biodiversity data, information and forecasts so that they are readily accessible to policymakers, managers, experts and other users. Conceived as a set of web based services, DOPA provides a broad set of free and open source tools to assess, monitor and even forecast the state of and pressure on protected areas at local, regional and global scale. DOPA Explorer 1.0 is a web based interface available in four languages (EN, FR, ES, PT) providing simple means to explore the nearly 16,000 protected areas that are at least as large as 100 km2. Distinguishing between terrestrial, marine and mixed protected areas, DOPA Explorer 1.0 can help end users to identify those with most unique ecosystems and species, and assess the pressures they are exposed to because of human development. Recognized by the UN Convention on Biological Diversity (CBD) as a reference information system, DOPA Explorer is based on the best global data sets available and provides means to rank protected areas at the country and ecoregion levels. Inversely, DOPA Explorer indirectly highlights the protected areas for which information is incomplete. We finally invite the end-users of DOPA to engage with us through the proposed communication platforms to help improve our work to support the safeguarding of biodiversity.JRC.H.5-Land Resources Managemen

The Digital Observatory for Protected Areas (DOPA) Explorer 1.0

The Digital Observatory for Protected Areas (DOPA) has been developed to support the European Union’s efforts in strengthening our capacity to mobilize and use biodiversity data, information and forecasts so that they are readily accessible to policymakers, managers, experts and other users. Conceived as a set of web based services, DOPA provides a broad set of free and open source tools to assess, monitor and even forecast the state of and pressure on protected areas at local, regional and global scale. DOPA Explorer 1.0 is a web based interface available in four languages (EN, FR, ES, PT) providing simple means to explore the nearly 16,000 protected areas that are at least as large as 100 km2. Distinguishing between terrestrial, marine and mixed protected areas, DOPA Explorer 1.0 can help end users to identify those with most unique ecosystems and species, and assess the pressures they are exposed to because of human development. Recognized by the UN Convention on Biological Diversity (CBD) as a reference information system, DOPA Explorer is based on the best global data sets available and provides means to rank protected areas at the country and ecoregion levels. Inversely, DOPA Explorer indirectly highlights the protected areas for which information is incomplete. We finally invite the end-users of DOPA to engage with us through the proposed communication platforms to help improve our work to support the safeguarding of biodiversity

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