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@InProceedings{ViergeverACCEMMMOMTW:2016:WePlPu,
               author = "Viergever, Karin M. and Andrade Neto, Pedro Ribeiro de and 
                         Cardoso, Manoel Ferreira and Castillo, Miguel and Exbrayat, 
                         Jean-Francois and Middlemiss, Sarah and Milodowski, David and 
                         Mitchard, Edward T. A. and Ometto, Jean Pierre Henry Balbaud and 
                         Morel, Veronique and Tipper, Richard and Williams, Mathew",
          affiliation = "Ecometrica and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and {El 
                         Colegio de la Frontera Sur} and {The University of Edinburgh} and 
                         Ecometrica and {The University of Edinburgh} and {The University 
                         of Edinburgh} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and Ecometrica and {The University of Edinburgh} and {The 
                         University of Edinburgh}",
                title = "A webmapping platform for publishing, sharing and managing remote 
                         sensingderived data for forest protection",
                 year = "2016",
         organization = "SPIE Remote Sensing",
             abstract = "Ecometrica has developed a web mapping platform that makes it easy 
                         to access, organise, share, query and analyse spatial data on land 
                         cover and ecosystem services without requiring GIS or remote 
                         sensing expertise on the end user side. The platform is built on 
                         spatial cloud technology and brings together relevant data, areas 
                         of interest and people. It enables the move away from fragmented, 
                         offline and siloed data management to up to date, connected and 
                         controlled data curation, allowing improved stewardship of data. 
                         Essential functions include viewing and querying spatial data. 
                         Summary reports can be downloaded in both pdf and spreadsheet 
                         format. Access is secure but mapping applications can also be made 
                         publicly available. By providing access and analysis of expert 
                         spatial data layers, the platform can be used in various ways e.g. 
                         by publishing or sharing research results with peers, and 
                         providing practical and insightful advice to non-specialist end 
                         users, industry groups and policy makers. Depending on how a 
                         mapping application has been customized, end-users can obtain 
                         quantitative and qualitative information about resources, measure 
                         impacts and opportunities, check compliance to environmental 
                         legislation, monitor changes to vegetation, water and other 
                         resources. Ecometrica, together with partners in the UK, Mexico 
                         and Brazil, have collaborated on a UK Space Agency international 
                         partnership space programme (IPSP) project to Advance EO 
                         Applications in Forests. The key objective was to reduce 
                         deforestation and degradation by improving EO derived information 
                         management and forest change detection methods. The Ecometrica 
                         Mapping platform was used to establish regional EO Labs within the 
                         various partner organisations, e.g. ECOSUR in Mexico, INPE and 
                         FUNCATE in Brazil. In Mexico and Brazil the EO Labs enabled 
                         collaboration between research organisations and NGOs to develop 
                         applications for monitoring forest change in specified study areas 
                         and has enabled the compilation of previously unavailable regional 
                         EO and other spatial datasets into products that can be used by 
                         researchers and state governments. Data on forest loss was linked 
                         to dynamic earth system models developed by the University of 
                         Edinburgh and INPE, utilising the EO Labs to provide an intuitive 
                         and powerful environment in which non-expert end-users can 
                         investigate the results from the huge datasets produced by 
                         multi-run model simulations. The construction of pre-written 
                         queries into each application builds in the expert guidance 
                         required to query complex model data, which gives the data some 
                         value outside of single research institutions, and enables their 
                         application in land use management and planning. The EO Lab 
                         facility in ECOSUR, Mexico has enabled the systematic compilation 
                         of previously unavailable regional EO and related data assets into 
                         products that can be used by researchers and state governments. 
                         This paper will demonstrate and discuss various examples of 
                         mapping applications created on Ecometrica EO Labs for the project 
                         Advancing EO Applications in Forests, showing how cloud technology 
                         can enhance the field of forest protection. We will show examples 
                         that use EO-derived data for forest conservation and management 
                         and we will discuss current developments for collaborative data 
                         storage and curation functionality.",
  conference-location = "Edinburgh, United Kingdom",
      conference-year = "26-29 Sept.",
        urlaccessdate = "27 abr. 2024"
}


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