UNSUPERVISED CLASSIFICATION OF RAPIDEYE IMAGES IN THE MAPPING OF LAND COVERAGE OF DELTA DO PARNAÍBA, PIAUÍ

Authors

DOI:

https://doi.org/10.26895/geosaberes.v12i0.1069

Keywords:

GIS, Digital image processing, Coastal

Abstract

The aim of this paper was the mapping of the land cover classes in an area of the Delta do Parnaíba, Piauí, NE, Brazil using the unsupervised classification method in RapidEye images. Through digital processing of images in a GIS environment, it was possible to map 12 classes of land cover. The results showed that the highest percentage of the study area is covered by fields with the presence of shrub vegetation and a predominance of pasture. Other classes (mobile dunes and sandy shoreline, undergrowth and exposed land) characterize a high level of environmental vulnerability and risk of erosion, illustrating the need for sustainable management techniques. Based on the techniques and evaluation criterias, the mapping indicated very good agreement, emphasizing the quality of the visual interpretation of the image and the classification method employed.

Author Biographies

  • João Victor Alves Amorim, Federal University of Piauí (UFPI), Brazil

    Master of Geography at the Post-graduate degree in Geography from the Federal University of Piauí (UFPI), Brazil.

  • Gustavo Souza Valladares, Federal University of Piauí (UFPI), Brazil

    Professor of Graduate and Postgraduate Geography, Federal University of Piauí (UFPI), Brazil.

  • Mirya Grazielle Torres Portela, Federal University of Piauí (UFPI), Brazil

    PhD in Agronomy by the Postgraduate Program in Agronomy, Tropical Agriculture at the Federal University of Piauí (UFPI), Brazil.

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Published

2021-02-01

Issue

Vol. 12 (2021)

Section

Artigos

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How to Cite

UNSUPERVISED CLASSIFICATION OF RAPIDEYE IMAGES IN THE MAPPING OF LAND COVERAGE OF DELTA DO PARNAÍBA, PIAUÍ. (2021). Geosaberes, 12, 88-106. https://doi.org/10.26895/geosaberes.v12i0.1069