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@InProceedings{PettaOharMede:2005:DeStBr,
               author = "Petta, Reinaldo Ant{\^o}nio and Ohara, Tomoyuki and Medeiros, 
                         Cleyber Nascimento de",
          affiliation = "{Universidade Federal do Rio Grande do Norte (UFRN). Departamento 
                         de Geologia.} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Universidade Federal do Rio Grande do Norte (UFRN). 
                         Departamento de Geologia.}",
                title = "Desertification studies in the brazilian northeastern areas with 
                         GIS database",
            booktitle = "Anais...",
                 year = "2005",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria 
                         Garcia",
                pages = "1053--1062",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 12. (SBSR)",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "CBERS-2, CCD, Caatinga vegetation, seasonal vegetation behavior, 
                         vegeta{\c{c}}{\~a}o da Caatinga, comportamento sazonal da 
                         vegeta{\c{c}}{\~a}o.",
             abstract = "This paper provides spatial and georeferenced information related 
                         to the susceptibility to desertification of several areas of the 
                         Northeast of Brazil. We aim to test the usefulness of spatial 
                         analysis methodologies to capture spatial-temporal heterogeneity 
                         from environmental gradients, for the assessment of 
                         desertification process at Remote Sensing data. In this sense, the 
                         analysis and integration of geo-environmental variables and the 
                         creation of environmental indicators associated with the 
                         development of the desertification process was performed, based on 
                         the use of spatial modeling procedures applied to data from the 
                         semi-arid portion of the Northeastern Brazil region. A set of 
                         sixteen-year period of Landsat 5-TM and Landsat 7 ETM+ images were 
                         explored for vegetation and soil study and local analysis of 
                         association and variability of spectral data were performed. The 
                         integration of the georeferenced data, related to these 
                         indicators, allowed the identification of five different levels of 
                         susceptibility to desertification (very high, high, moderate, low 
                         and very low), and the geographic domain of each class. Based on 
                         the analysis of the dynamics of the vegetation cover and on the 
                         evaluation of field data, we can establish that the main results 
                         refer that there is a decrease of the biomass at the region, 
                         associated either with the dense caatinga vegetation areas, but 
                         more important, with the scrub and degraded areas. From an 
                         environmental perspective, the decreasing biomass level associated 
                         with scrub and degraded areas are according to the negative 
                         feedbacks of the desertification process. Considering the last 
                         ten-year periods of comparisons, the spatial variances leave 
                         almost different, which means that heterogeneity pattern, is 
                         increasing very considerably. This fact means an explicit 
                         expansion of spatial heterogeneity of the desertification 
                         landscapes, during the last years. KeyWords: Desertification, 
                         Environmental Indicators, Environmental Analysis, Susceptibility, 
                         Geoprocessing, Geographic Information Systems (GIS), Spatial 
                         Modeling, Semi-arid, Northeastern region, Serid{\'o}, Rio Grande 
                         do Norte, Brazil.",
  conference-location = "Goi{\^a}nia",
      conference-year = "16-21 abr. 2005",
                 isbn = "85-17-00018-8",
             language = "Ingl{\^e}s",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "ltid.inpe.br/sbsr/2004/11.20.14.29",
                  url = "http://urlib.net/rep/ltid.inpe.br/sbsr/2004/11.20.14.29",
           targetfile = "1053.pdf",
                 type = "Avalia{\c{c}}{\~a}o e Aplica{\c{c}}{\~o}es do CBERS",
        urlaccessdate = "19 jan. 2021"
}


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