期刊
BOLETIM DE CIENCIAS GEODESICAS
卷 25, 期 1, 页码 -出版社
UNIV FEDERAL PARANA, CENTRO POLITECNICO
DOI: 10.1590/s1982-21702019000100002
关键词
Forest mapping; Amazonia; ALOS/PALSAR-2; remote sensing; forest monitoring
资金
- Coordination for the Improvement of Higher Education Personnel (CAPES)
- Brazilian National Council for Scientific and Technological Development (CNPq)
- National Institute for Space Research (INPE)
- Chico Mendes Institute of Biodiversity Conservation (ICMBio) [38157-5]
- Large Scale Biosphere-Atmosphere Experiment in Amazonia Program (LBA/Santarem)
- European Union's Horizon 2020 Research and Innovation Programme under the Marie Skoodowska-Curie grant [660020]
- Marie Curie Actions (MSCA) [660020] Funding Source: Marie Curie Actions (MSCA)
This study aims to analyze the capability of the target decomposition techniques and the polarimetric ratios applied to the ALOS/PALSAR-2 satellite polarimetric images to discriminate the land use and land cover classes in the Tapajos National Forest region, Para State. Three full polarimetric ALOS/PALSAR-2, level 1 single look complex scenes were selected to generate the coherence and the covariance matrices to derive the Cloude-Pottier and the Freeman-Durden target decomposition attributes. From the radiometrically calibrated PALSAR-2 images, we generated the backscatter coefficients, the cross polarized ratio (RC; HV/HH), the parallel polarized ratio (RP; VV/HH) and the Radar Forest Degradation Index (RFDI). The images resulting from these polarimetric attributes were processed by the Maximum Likelihood (MAXVER) classifier coupled with the Iterated Conditional Modes (ICM) contextual algorithm. We found that the classifications derived from the target decomposition attributes, mainly from the Cloude-Pottier technique, with a Kappa index of 0.75, presented a significant higher performance than those derived from the RC ratio, RP ratio, and RFDI.
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