Anuário do Instituto de Geociências (Aug 2018)

Use of Multispectral Images in the Analysis of Vegetation Cover in a Forest Concession Area in Rondônia

  • Camila Vieira Martins ,
  • Adriano Reis Prazeres Mascarenhas

DOI
https://doi.org/10.11137/2018_2_104_116
Journal volume & issue
Vol. 41, no. 2
pp. 104 – 116

Abstract

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In Brazil, the concession of public forests for logging is a government initiative to curb illegal exploration and occupation in order to preserve the national patrimony. However, the knowledge about the impacts promoted in this way of exploration is incipient, considering that field data collection can be lengthy and costly. Therefore, geotechnology is inserted in this context by presenting methods of obtaining information with speed and relative precision. So, the objective of this work was to analyze the vegetation cover variation in a public forest area under different logging intensities in the forest concession regime, applying multispectral images and the normalized difference vegetation index (NDVI). The study site was the Jamari National Forest, where two areas were explored for two consecutive years: the Annual Production Unit 01 (UPA 01) with cutting intensities of 9 m³ ha- ¹ and 10.5 m³ ha- ¹ in 2010 and 2011, respectively, and the Annual Production Unit 02 (UPA 02), with cutting intensities of 24 m³ ha- ¹ and 3 m³ ha- ¹, in 2012 and 2013, respectively. The analyzes were performed before, during and after logging and the results were submitted to the paired t-test (p <0.05). In the UPA 01, except between the years 2011 and 2012, there were no significant differences in the values of vegetal cover. Regarding UPA 02, there were no differences in any of the periods evaluated. In this way, it was possible to verify the effect of the forest exploitation and to estimate the vegetation cover, however, the use of geotechnologies for this purpose is complementary to the field monitoring, since NDVI values are subject to natural or anthropogenic environmental interventions, being able to underestimate or overestimate the results

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