Bioscience Journal (Jun 2019)

Space-time variability of the Roncador river basin in the change of land use and cover and its correlation with climatic variables

  • Raquel de Oliveira Santos,
  • Rafael Coll Delgado,
  • Marcos Gervasio Pereira,
  • Leonardo Paula de Souza,
  • Paulo Eduardo Teodoro,
  • Carlos Antonio da Silva Junior,
  • Giovani Glaucio de Oliveira Costa

DOI
https://doi.org/10.14393/BJ-v35n4a2019-39486
Journal volume & issue
Vol. 35, no. 4

Abstract

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The objective of this study was to evaluate the space-time dynamics of the soil use and occupation of the Rio Roncador river basin between 1985 and 2010. The scenes were classified by two methods (partially unsupervised - K-Means and supervised - Maximum likelihood), the Thematic Mapper sensor products on the LANDSAT 5 orbital platform were used for both images of a 25-year time series (1985 to 2000). In order to measure the accuracy of the field the computer application Google Earth was used, in which nine classes (urban area, agricultural area, pasture, exposed soil, native forest, secondary vegetation, mangrove, altitude field and water) were collected. A multiple linear regression was performed, correlating the Normalized Difference Vegetation Index - mean NDVI (dependent variable) with the independent climatic variables (global solar radiation - MJm-2day-1, average air temperature - °C, relative humidity -%, evapotranspiration - mm d-1, and rain - mm). According to the general classification by Kappa parameter of the images for 2005 and 2010, they were identified as very good (68% and 74%). These results confirm that the Roncador River Basin is undergoing transformation in its landscape, with an average reduction of -49% in native vegetation areas due to the increase in urban areas (25%) and agriculture (31%). The statistical analysis showed that rainfall and air temperature were the only variables that presented significant sigma (0.04) and (0.02). The obtained coefficient of determination indicated that 47% of the variations of the "vegetation index" are explained by the environmental variables.

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