SPECTRAL-TEMPORAL PROFILE ANALYSIS OF MAIZE, SOYBEAN AND SUGARCANE BASED ON OLI/LANDSAT-8 DATA

Authors

  • Bruno Montibeller University of Tartu
  • Ieda Del'Arco Sanches National Institute for Space Research
  • Alfredo José Barreto Luiz Embrapa Environment
  • Fabio Gonçalves Canopy Remote Sensing Solutions
  • Daniel Alves de Aguiar Agrosatélite Geotecnologia Aplicada

DOI:

https://doi.org/10.37856/bja.v94i3.3612

Abstract

Remote sensing (RS) technology is a viable complementary alternative to current agriculture surveying methods. RS data spectral information is the main variable used for several purposes, such as crop type identification. However, different management practices (MP) adopted in crop cultivation may alter its spectral characteristics. The objective of this work is to analyze the spectral-temporal profile (STP) variation of soybean, maize and sugarcane cultivated under different MP. We used time series of the six spectral bands of the OLI/Landsat-8 sensor and of two vegetation indexes (VI) to investigate the intraspecific variation (same crop specie) and the interspecific variation (different crop species). We applied hierarchical cluster analyses to determine the crop´s STP variation. The bands results were more efficient than the VI. This shows that despite the widely use of VI, better results are retrieved when using the bands STP, which also allows differentiating and analyzing crops cultivated under different MP.

Author Biographies

Bruno Montibeller, University of Tartu

PhD student at University of Tartu

Ieda Del'Arco Sanches, National Institute for Space Research

Researcher at National Institute for Space Research

Alfredo José Barreto Luiz, Embrapa Environment

Researcher at Embrapa Environment

Fabio Gonçalves, Canopy Remote Sensing Solutions

Co-founder & CEO at Canopy Remote Sensing Solutions

Daniel Alves de Aguiar, Agrosatélite Geotecnologia Aplicada

Director at Agrosatélite Geotecnologia Aplicada

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Published

2019-12-23

Issue

Vol. 94 No. 3 (2019)

Section

Artigos