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

Abstract

-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 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. Despite the availability of the agreed WPS standard for Web-based geospatial modeling, few practical implementations exist, making eHabitat a significant addition to the field. On the other hand, the wide uptake of Web access standards for geospatial data has led to a wealth of data sources within GEOSS which can be effectively combined using eHabitat. 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.

Indicators for Assessing Habitat Values and Pressures for Protected Areas—An Integrated Habitat and Land Cover Change Approach for the Udzungwa Mountains National Park in Tanzania

“…The results serve as an example of how eHabitat+ allows for large-scale analyses of PAs using continent-wide consistent datasets for producing key landscape indicators, identifying unique ecological areas that are currently unprotected and allowing results to be easily compared at global level through the DOPA [7,17]. Moreover, the integrative analysis of these habitat data with accurate LULCC information as derived from the IMPACT toolbox, allows potential pressures on ecological high value areas to be highlighted and thus serves as an effective decision support instrument.…”

“…2016, 8,862 3 of 20 zone (20 km) with particular attention to the wildlife corridors which connect the PA to other conservation areas [16]. This was addressed in three ways: (1) application of an existing methodology to identify habitats and existing ecologically similar areas outside the UMNP, which are potentially useful for wildlife and their movements [17,18]; (2) assessment of the impact of human activities over time through land use/land cover (LULC) conversions inside the UMNP and especially in the surroundings, including non-protected areas and defined wildlife corridors through the analysis of satellite image time series [19]; (3) integration of the habitat similarity maps with the LULCC data to detect anthropogenic pressure caused by agriculture and urbanization to existing corridors and potentially new corridors. The importance and uniqueness of this study lies in the combination of existing methods and tools to automatize the identification of habitats with potentially high biodiversity and the assessment of pressures to these.…”

“…In addition to the LULC maps obtained through the IMPACT toolbox, eHabitat+ was used to investigate the presence of different functional habitat types in this PA, based on a quantitative biophysical approach [17,30].…”

Geospatial data sharing, online spatial analysis and processing of Indian Biodiversity data in Internet GIS domain – A case study for raster based online geo-processing

“…The services describes a mechanism by which a client computer may submit a job to be processed on a server computer, using data provided as a WFS (Vector) or WCS (Raster). It is client/server architecture, meaning that both a client component and a server component are mandatory (Anthony et al, 2013 ;Dubois et al, 2013 ) For implementation and testing purposes it is useful to build the client-side application on a GIS to take advantage of existing services or develop their own services (Christopher et al, 2009). …”

“…Some important works have been done by using online geoprocessing such as the shortest path between two points (PML: Shortest path), systematic planning and cultivation of agricultural fields (Bruin et al, 2014), ecological modeling and forecasting, forecast the impact of climate change on protected areas (Dubois et al, 2013) ,process geospatial data such as NDVI calculation on different computing backend (Giuliani et al, 2012 ), Geostatistical computing and INTAMAP: The design and implementation of an interoperable automated interpolation web service (Pebesma et al, 2011 ), thematic map generation (Rautenbach et al, 2013 ) and Forecasting biomes of protected areas (Skoien et al,2011 ) etc.…”