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ABSTRACT

When defining indicators on the environment, the use of existing initiatives should be a priority rather than redefining indicators each time. From an Information, Communication and Technology perspective, data interoperability and standardization are critical to improve data access and exchange as promoted by the Group on Earth Observations. GEOEssential is following an end-user driven approach by defining Essential Variables (EVs), as an intermediate value between environmental policy indicators and their appropriate data sources. From international to local scales, environmental policies and indicators are increasingly percolating down from the global to the local agendas. The scientific business processes for the generation of EVs and related indicators can be formalized in workflows specifying the necessary logical steps. To this aim, GEOEssential is developing a Virtual Laboratory the main objective of which is to instantiate conceptual workflows, which are stored in a dedicated knowledge base, generating executable workflows. To interpret and present the relevant outputs/results carried out by the different thematic workflows considered in GEOEssential (i.e. biodiversity, ecosystems, extractives, night light, and food-water-energy nexus), a Dashboard is built as a visual front-end. This is a valuable instrument to track progresses towards environmental policies.  相似文献   
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In spite of widely documented studies of deforestation rates and land use/cover changes in tropical dry forests in Mexico, relatively little is known about fragmentation patterns in such forests. This study defines the spatial distribution of landforms and land use/cover types the lower Papagayo River basin and examines their influence on fragmentation patterns and biological diversity in a tropical dry forest in that southern Pacific region. The land use/cover map was constructed from aerial photographs, Landsat TM imagery (2000) and fieldwork. Landform units were defined based on altitude, slope, lithology and morphology. Landscape fragmentation parameters were obtained using FRAGSTATS (version 3.3) considering the numbers of patches, mean, minimum and maximum patch size, edge density, total edge and connectivity. Results show tropical dry forest to be remnant vegetation (~11 per cent), characterized by isolation and low connectivity. Land use/cover types have different effects on fragmentation patterns. Agriculture and cattle raising produce similar numbers of patches, but with a different mean size; and human settlements have a scattered distribution pattern. The abandonment of rural agricultural livelihoods has favoured the expansion of secondary tropical dry forest characterized by continuity and high connectivity, which suggests a high regeneration potential from land abandonment. It can be concluded that tropical dry forest fragmentation and recovery at regional scales depend on such landscape attributes as lithology, slope, geomorphology and management.  相似文献   
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Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.  相似文献   
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ABSTRACT

In recent years, researchers of different communities have increased their efforts in formalizing a set of measurements regularly collected for analysing changes in Drivers, States, Impacts and Responses of a given discipline. In some cases, different actors have converged in a minimum set of Essential Variables (EVs), such as for Climate, Biodiversity or Oceans. The definition of such EVs is an ongoing evolution and in extension (e.g. EVs for water) although some communities have not even started (e.g. agriculture and energy). This paper characterizes the Earth Observation (EO) networks and creates a graph representation of their relations. Secondly, this graph is enriched with the EVs produced by each network creating a knowledge base. Finally, an effort has been done to identify links between EVs and Sustainable Development Goals (SDG) indicators in a way that they indirectly connect the EO. An analysis to detect gaps in EO variables due to a lack of observational networks is performed. Several suggestions for improving SDG indicators framework by considering EVs are exposed, as well as proposing new necessary EVs and suggesting new EO based indicators. The complete graph is available in the ENEON website (http://www.eneon.net/graph-ev-sdg/).  相似文献   
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