Using remote sensing images for stratification of the cerrado in forest inventories

Authors

  • Sérgio Teixeira da Silva Universidade Federal de Lavras, Departamento de Ciências Florestais
  • José Marcio de Mello Universidade Federal de Lavras, Departamento de Ciências Florestais
  • Fausto Weimar Acerbi Junior Universidade Federal de Lavras, Departamento de Ciências Florestais
  • Aliny Aparecida dos Reis Universidade Federal de Lavras, Departamento de Ciências Florestais
  • Marcel Regis Raimundo Universidade Federal de Lavras, Departamento de Ciências Florestais
  • Iasmim Louriene Gouveia Silva Universidade Federal de Lavras, Departamento de Ciências Florestais
  • José Roberto Soares Scolforo Universidade Federal de Lavras, Departamento de Ciências Florestais

DOI:

https://doi.org/10.4336/2014.pfb.34.80.742

Keywords:

Systematic sampling, Tratified Random Sampling, Visual image interpretation, Remote Sensing

Abstract

Remote sensing imagery can be a very useful auxiliary tool for native forests inventory. Thus, the objective of this study was to evaluate the stratification of a cerrado (Brazilian savanna) patch based on visual image interpretation techniques as well as to compare the errors from two sampling designs, the Stratified Random Sampling (SRS) and the Systematic Sampling (SS).The study area corresponds to a cerrado sensu stricto patch located in the municipality of Papagaios, Minas Gerais, Brazil. The cerrado wood volumes were obtained from a forest inventory field campaign where 32 plots were measured systematically. The study area was stratified based on a visual interpretation of a Landsat 5 TM image, and the strata formed were: "Strata I", "Strata II", "Strata III", water and riparian forests. There was a reduction of 43% on the inventory errors using the SS estimators compared to the inventory errors using the SRS estimators. We concluded that the stratification based on image interpretation techniques was efficient since there was a reduction on the cerrado inventory errors.

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Author Biographies

Sérgio Teixeira da Silva, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/1113069509372599

José Marcio de Mello, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/9805647108156583

Fausto Weimar Acerbi Junior, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/5979975754477865

Aliny Aparecida dos Reis, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/5364437916631071

Marcel Regis Raimundo, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/2469638959423651

Iasmim Louriene Gouveia Silva, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/1734331013083092

José Roberto Soares Scolforo, Universidade Federal de Lavras, Departamento de Ciências Florestais

http://lattes.cnpq.br/8717150703694552

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Published

2014-12-30

How to Cite

SILVA, Sérgio Teixeira da; MELLO, José Marcio de; ACERBI JUNIOR, Fausto Weimar; REIS, Aliny Aparecida dos; RAIMUNDO, Marcel Regis; SILVA, Iasmim Louriene Gouveia; SCOLFORO, José Roberto Soares. Using remote sensing images for stratification of the cerrado in forest inventories. Pesquisa Florestal Brasileira, [S. l.], v. 34, n. 80, p. 337–343, 2014. DOI: 10.4336/2014.pfb.34.80.742. Disponível em: https://pfb.sede.embrapa.br/pfb/article/view/742. Acesso em: 19 apr. 2025.

Issue

Vol. 34 No. 80 (2014): out./dez.

Section

Articles

License

Copyright (c) 2014 Sérgio Teixeira da Silva, José Marcio de Mello, Fausto Weimar Acerbi Junior, Aliny Aparecida dos Reis, Marcel Regis Raimundo, Iasmim Louriene Gouveia Silva, José Roberto Soares Scolforo

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