USE OF ARTIFICIAL NEURAL NETWORKS FOR FORESTRY BIODIVERSITY ESTIMATION

  • Henrique Galetto Ribeiro CENTRO UNIVERSITÁRIO SÃO CAMILO
  • Daniel Henrique Breda Binoti CENTRO UNIVERSITÁRIO SÃO CAMILO
  • Nubia Ponce Leão de Oliveira Escola Estadual de Ensino Fundamental e Médio de Jeronimo Monteiro
  • Leonardo Marques Rodrigues Escola Estadual de Ensino Fundamental e Médio de Jeronimo Monteiro
  • Armino Cezar Silva França Escola Estadual de Ensino Fundamental e Médio de Jeronimo Monteiro

Abstract

This work aims to estimate unequal forest stand characteristics such as biodiversity, biomass, carbon content and forest restoration indexes, as well as estimate the population size of threatened species in forest fragments from remote sensing data (Band and Index Values) and artificial intelligence tools. For this study we used floristic inventory data provided by AMBINOVA Company. For each plot, we estimated the number of species, Shannon-Weaver floristic diversity index, and the input values for landsat 5 bands 1, 2, 3, 4, 5 and 7 and NDVI, SAVI and EVI indices. the use of artificial neural networks. The results showed a correlation between observed and estimated values of 90%, demonstrating the feasibility of the tool for estimating biodiversity indexes.

Published
Oct 21, 2021
How to Cite
RIBEIRO, Henrique Galetto et al. USE OF ARTIFICIAL NEURAL NETWORKS FOR FORESTRY BIODIVERSITY ESTIMATION. Cadernos Camilliani e-ISSN: 2594-9640, [S.l.], v. 16, n. 4, p. 1754-1770, oct. 2021. ISSN 2594-9640. Available at: <http://www.saocamilo-es.br/revista/index.php/cadernoscamilliani/article/view/427>. Date accessed: 17 may 2024.
Citation Formats
Issue
Vol 16 No 4 (2019): Cadernos Camilliani - e-ISSN: 2594-9640
Section
Artigos