Land use and land cover mapping in the Brazilian Amazon using polarimetric airborne P-band SAR data

C. Freitas, L. de Souza Soler, S.J.S. Sant' Anna, L.V. Dutra, J.R. dos Santos, J.C. Mura, A.H. Correia

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49 Citations (Scopus)


In September 2000, an airborne synthetic aperture radar (SAR) mission acquired unprecedented full polarimetric P-band data over the Tapajos National Forest (Para State), which is an area in the Brazilian Amazon which has been continuously monitored in the last three decades. Eight land use/cover classes were identified, namely, primary forest, regeneration older than 25 years, regeneration between 12 and 25 years, regeneration between 6 and 12 years, regeneration younger than six years, crops/pasture, bare soil, and floodplain (FP). The objective of this paper is to analyze the potential of full polarimetric P-band data in distinguishing different land use/cover classes with a minimum established Kappa value of 75%, using the latest development on SAR statistical characterization. The iterated conditional mode (ICM) contextual classifier was applied to amplitude, intensity images, biomass index, and some polarimetric parameters (entropy, alpha angle, and anisotropy) extracted from the polarimetric P-band data. As the accuracy obtained for eight classes was not acceptable, another two sets, with five and four classes, were formed by the combination of the previous ones. They were defined by confusion matrix analysis and by the graphical analysis of average backscatter values, entropy, [alpha] angle, and anisotropy images and by the H/alpha plans of the land use samples. The classification accuracy with four classes (three levels of biomass plus FP) was then considered acceptable with a Kappa value of 76.81%, using the ICM classification with the adequate bivariate distribution for the HV and VV channels.
Original languageEnglish
Pages (from-to)2956-2970
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number10
Publication statusPublished - 2008


  • tropical rain-forest
  • radar backscatter
  • unsupervised classification
  • colombian amazon
  • pine stands
  • biomass
  • images
  • multifrequency
  • deforestation
  • decomposition


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