Utilization of analogic data of Landsat-TM on screening vegetation of part of the Nhecolândia subregion of the Brazilian Pantanal

Authors

  • Myrian de Moura Abdon
  • João dos Santos Vila da Silva
  • Vali Joana Pott
  • Arnildo Pott
  • Marta Pereira da Silva

DOI:

https://doi.org/10.1590/S1678-3921.pab1998.v33.5052

Keywords:

vegetation mapping, remote sensing, geographic information system

Abstract

The objective of this work was to discriminate the phytophysiognomies of part of the Nhecolândia subregion in the Brazilian Pantanal, through analogic data of Landsat-TM, aiming at assist management of cattle and wildlife. This area of wetland is characterized by variations in vegetation density, floristic composition and soil moisture. Satellite image 1:50,000 obtained during the dry season (Oct. 21, 1990) was used. The method was visual interpretation of Landsat image. Sites with different vegetation types were selected. Ground truthing was done on these points on the images, using Global Positioning System (GPS). A 1:50,000 vegetation chart was generated, distinguishing the following phytophysiognomies: 1) "Cerradão" woodland; 2) "Cerrado" savanna or dense "cerrado" savanna; 3) Open "cerrado" savanna; 4) Grassland with "cerrado" patches; 5) Grassland; 6) Channel grassland with gallery forest islets; 7) Aquatic vegetation and shrubs. The spacialized products were stored in a Geographic Information System (GIS). The results demonstrated to be sufficiently adequate to distinguish the various vegetation types present in the region, giving important fundaments for characterization and management of the large rural properties, as well as of wildlife.

Published

1998-12-01

How to Cite

Abdon, M. de M., Silva, J. dos S. V. da, Pott, V. J., Pott, A., & Silva, M. P. da. (1998). Utilization of analogic data of Landsat-TM on screening vegetation of part of the Nhecolândia subregion of the Brazilian Pantanal. Pesquisa Agropecuaria Brasileira, 33(13), 1799–1813. https://doi.org/10.1590/S1678-3921.pab1998.v33.5052

Issue

Section

REMOTE SENSING