@InProceedings{AmaralCosAraXimRen:2013:VaAmMo,
               author = "Amaral, Silvana and Costa, Cristina Bestetti and Arasato, Luciana 
                         Satiko and Ximenes, Arimat{\'e}a de Carvalho and Renn{\'o}, 
                         Camilo Daleles",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "AMBDATA: Vari{\'a}veis ambientais para Modelos de 
                         Distribui{\c{c}}{\~a}o de Esp{\'e}cies (SDMs)",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "6930--6937",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Species distribution models (SDMs) provide the geographical 
                         distribution of a species based on the definition of it potential 
                         ecological niche, from the relation between species occurrences 
                         and environmental characteristics. As SDMs have been widely used 
                         for biodiversity studies at regional scale, there are increase 
                         demands for different environmental data in a standardized format. 
                         In order to facilitate the manipulation of these geographical 
                         datasets, at this paper we present Ambdata: a website created to 
                         provide environmental variables from official data sources useful 
                         for SDMs purpose. Environmental variables related to climate 
                         (monthly minimum, maximum, and mean temperature; monthly 
                         precipitation; and bioclimatic data), topography (altitude, slope, 
                         aspect, drainage density, vertical height to the closest 
                         drainage), soil and vegetation characteristics, usually used for 
                         SDMs, were first acquired, produced and then organized in a 
                         geographical information system. Each variable was resampled to 
                         spatial resolution of 30 arc-seconds (approximately 1 km), 
                         converted to Lat-Long geographical projection, and clipped to the 
                         geographical boundaries of Brazil and Brazilian Amazon. Once the 
                         ascii-raster grid files were prepared, we organized a webpage 
                         called Ambdata that describes the dataset and provides free access 
                         to these data. This articles contributes to present Ambdata 
                         webpage to the scientific community: a database available to 
                         assist SDM studies of Amazon and Brazilian species, improving the 
                         knowledge about our biodiversity.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "944",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GH36",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GH36",
           targetfile = "p0944.pdf",
                 type = "Monitoramento e Modelagem Ambiental",
        urlaccessdate = "09 maio 2024"
}