Revista Geama (Oct 2016)

Use of geotechnology in analysis of forest biomass in the state of Paraiba | Uso da geotecnologia na análise da biomassa florestal no estado da Paraíba

  • Ivan de Almeida Machado Coelho,
  • Rafael Abrahão,
  • Simone Mirtes Araújo Duarte

Journal volume & issue
Vol. 2, no. 4
pp. 407 – 416

Abstract

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The GIS is considered one of the most important tools for understanding the structure and dynamics of vegetation cover in various temporal and spatial scales, when used in the landscape’s ecology provides information for man's relationship study of the environment, and to understand ecological processes. This study aimed to show the role of digital processing techniques of unsupervised images for multitemporal analysis of environmental degradation in the state of Paraiba. The study area for this work it was the state of Paraiba, in Mesoregions of Sertão Paraibano, Borborema and Agreste Paraibano. Rainfall is unevenly distributed throughout the year, with diverse climatic conditions, associated to the climate distribution with location, noting in the closer regions to the coast a humidity climate, although how further away from coast, drier is the regions. The methodology was based on temporal analysis of orbital images TM / Landsat - 5 for the dates in September 1998 and September 2009 for mesoregion of Sertão Paraibano, in October 1999 and September 2008 to the mesoregion of Borborema, and in April 1999 and July 2007 to the mesoregion of Agreste Paraibano, where the images used were obtained from the National Institute for Space Research (INPE). The results indicated that the temperature and rainfall are directly related to the amount of vegetation cover, increased sparse vegetation appears to be quite worrying because it is in this class that degradation levels can increase beginning to desertification cores. The work showed the great potential of using geoprocessing tools for spatial analysis of the study area and from that conduct a study on the dynamics of vegetation cover in the study area.

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