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Definition of candidate Essential Variables for the monitoring of mineral resource exploitation

Geo-Spatial Information Science 2019年第4期22卷 265-278,I0004页

作者： Mariapaola Ambrosone Grégory Giuliani Bruno Chatenoux denisa rodila Pierre Lacroix Institute for Environmental Sciences University of GenevaGenevaSwitzerland United Nations Environment Programme Global Resource Information Database(GRID)GenevaSwitzerland

The practice of raw material extraction has a high impact on the environment and represents a potential threat to the health and thriving of local *** concept of Extractive Essential Variables(EEVs)are explored in order to propose variables that can be used to quantify the environmental footprint of mineral *** the interdependence of mining activities with social,economic and environmental issues,the variables target the development of monitoring tools for the implementation of the Sustainable Development Goals(SDGs).The identification of EEVs is based on the use of Earth Observation products in the field of mineral resources exploitation.A list of variables is proposed based on three classes of Essential Variables(EVs):installation and exploration phase,mineral extraction,and ore *** variables take into account the impacts of mining on the hydrology,land,water resources and the atmosphere of the area subjected to mineral *** of the variables is implemented as an operational workflow addressing SDG15,“life on land”.The workflow is intended to assess the area of forest ecosystem lost due to the presence of a mining *** data on the extent of mining concessions and forest cover are combined using ArcGIS^(TM).The workflow is successively translated into a Unix script to automatize the process of data *** script is developed using the Geospatial Data Abstraction Library(GDAL).The use of a Virtual Laboratory Platform(VLab),a web-service-based access platform,increases the accessibility of data and resources and the re-use of the *** work is a first attempt to propose a framework of EEVs,derived data workflows,while the underlying methodology,partially based on scientific publications and on personal reasoning,still needs to be tested and,improved based on expertise in the sector.

关键词： Earth observation mineral extraction sustainable development Extractive Essential Variables(EEVs) environmental indicator Sustainable Development Goal(SDG) data workflow

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GEOEssential–mainstreaming workflows from data sources to environment policy indicators with essential variables

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International Journal of Digital Earth 2020年第2期13卷 322-338页

作者： Anthony Lehmann Stefano Nativi Paolo Mazzetti Joan Maso Ivette Serral Daniel Spengler Aidin Niamir Ian McCallum Pierre Lacroix Petros Patias denisa rodila Nicolas Ray Grégory Giuliani enviroSPACE Institute for Environmental SciencesUniversity of GenevaGenevaSwitzerland Dpt.F.-A.Forel for Environment and Water Sciences Faculty of SciencesUniversity of GenevaGenevaSwitzerland National Research Council of Italy–Institute of Atmospheric Pollution Research Sesto Fiorentino(FI)Italy CREAF Grumets research group CREAF.Edifici C.Universitat Autònoma de BarcelonaBellaterraSpain Remote Sensing Section Helmholtz Center Potsdam GFZ German Research Center for GeosciencesPotsdamGermany Senckenberg Biodiversity and Climate Research Institute Senckenberg Gesellschaft für NaturforschungFrankfurt am MainGermany International Institute for Applied Systems Analysis LaxenburgAustria GRID-Geneva Institute for Environmental SciencesUniversity of GenevaGenevaSwitzerland School of Surveying Engineering Aristotle University of ThessalonikiThessalonikiGreece GeoHealth Group Institute of Global HealthFaculty of MedicineUniversity of GenevaGenevaSwitzerland

When defining indicators on the environment,the use of existing initiatives should be a priority rather than redefining indicators each *** 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 *** is following an end-user driven approach by defining Essential Variables(EVs),as an intermediate value between environmental policy indicators and their appropriate data *** international to local scales,environmental policies and indicators are increasingly percolating down from the global to the local *** scientific business processes for the generation of EVs and related indicators can be formalized in workflows specifying the necessary logical *** 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 *** interpret and present the relevant outputs/results carried out by the different thematic workflows considered in GEOEssential(***,ecosystems,extractives,night light,and food-water-energy nexus),a Dashboard is built as a visual *** is a valuable instrument to track progresses towards environmental policies.

关键词： SDGs environmental policies essential variables earth observation knowledge base workflows virtual research environment

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Building an Earth Observations Data Cube: lessons learned from the Swiss Data Cube (SDC) on generating Analysis Ready Data (ARD)

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Big Earth Data 2017年第1期1卷 100-117页

作者： Gregory Giuliani Bruno Chatenoux Andrea De Bono denisa rodila Jean-Philippe Richard Karin Allenbach Hy Dao Pascal Peduzzi Institute for Environmental Sciences/g D-geneva University of genevagenevaSwitzerland Institute for Environmental Sciences/EnviroSPaCE University of genevagenevaSwitzerland Institute for Environmental Sciences/Environmental governance and territorial Development University of genevagenevaSwitzerland Science Division United Nations Environment ProgrammegenevaSwitzerland

Pressures on natural resources are increasing and a number of challenges need to be overcome to meet the needs of a growing population in a period of environmental *** of these environmental issues can be monitored using remotely sensed Earth Observations(EO)data that are increasingly available from a number of freely and openly accessible ***,the full information potential of EO data has not been yet *** remain still underutilized mainly because of their complexity,increasing volume,and the lack of efficient processing *** Data Cubes(DC)are a new paradigm aiming to realize the full potential of EO data by lowering the barriers caused by these Big data challenges and providing access to large spatio-temporal data in an analysis ready *** and regular provision of Analysis Ready Data(ARD)will significantly reduce the burden on EO data ***,ARD are not commonly produced by data providers and therefore getting uniform and consistent ARD remains a challenging *** paper presents an approach to enable rapid data access and pre-processing to generate ARD using interoperable services *** approach has been tested and validated generating Landsat ARD while building the Swiss Data Cube.

关键词： Data Cube Earth Observations Landsat automatic processing analysis ready Data

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