2012
DOI: 10.1590/s0044-59672012000200004
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Análise do potencial de imagem TerraSAR-X para mapeamento temático no sudoeste da Amazônia brasileira

Abstract: ResumoO presente trabalho tem como objetivo analisar o potencial de imagens SAR polarimétricas do sensor TerraSAR-X, no modo StripMap, para mapear o uso e cobertura da terra na região sudoeste da Amazônia brasileira. No procedimento metodológico imagens de amplitude nas polarizações A HH e A VV , A derivada da matriz de covariância, bem como da entropia A Entropia derivada da decomposição de alvos por auto-valores fizeram parte, de forma individual ou combinada, do conjunto de dados investigados. Na c… Show more

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Cited by 4 publications
(5 citation statements)
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References 28 publications
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“…While the classification of clean pasture and shrubby pasture remains challenging, TS-X data constitutes an adequate data source for forest / non-forest mapping. The PA and UA for forest are higher compared to the accuracies achieved for the other classes, and are in accordance with the accuracies of comparable studies (Schlund et al, 2013;Garcia et al, 2011). While we did not perform specific analysis on the differences of HH-HV and VV-VH polarized data sets, Table 3 shows the OA of the internal HH-HV polarized scenes (06-30) to especially benefit from the multi-temporal integration, and also its neighboring scenes to benefit disproportionately.…”
Section: Discussionsupporting
confidence: 84%
See 1 more Smart Citation
“…While the classification of clean pasture and shrubby pasture remains challenging, TS-X data constitutes an adequate data source for forest / non-forest mapping. The PA and UA for forest are higher compared to the accuracies achieved for the other classes, and are in accordance with the accuracies of comparable studies (Schlund et al, 2013;Garcia et al, 2011). While we did not perform specific analysis on the differences of HH-HV and VV-VH polarized data sets, Table 3 shows the OA of the internal HH-HV polarized scenes (06-30) to especially benefit from the multi-temporal integration, and also its neighboring scenes to benefit disproportionately.…”
Section: Discussionsupporting
confidence: 84%
“…Figure 3 visualizes the classes considered in our classification scheme. The considered LULC classes match comparable studies using TS-X data in Brazilian, or tropical settings, respectively (Garcia et al, 2011;Schlund et al, 2013). As the time period of our study falls into the dry season between June and September, corresponding multispectral remote sensing data could be interpreted sufficiently well.…”
Section: Reference Datasupporting
confidence: 77%
“…Overall, our results confirm that PolSAR images are more efficient than dual-pol SAR images in mapping wetland land cover and vegetation types. PolSAR classification accuracies reported in the literature vary from 64% (Brisco et al, 2011) to 95% (Brisco et al, 2013), but more frequently between 75% and 90% (Ainsworth, Kelly, & Lee, 2009;Garcia, Roberto, Mura, Johann, & Kux, 2012;Lee, Grunes, & Pottier, 2001;Millard & Richardson, 2013;Qi et al, 2012;Sartori, Imai, Mura, Novo, & Silva, 2011). The accuracies yielded in this study ranged from κ~0.5 to 0.83, AD from~30% to 2% and QD from 15.3% to 3.33%.…”
Section: Polsar Responses To Vegetation Dynamicsmentioning
confidence: 56%
“…The polarization of the SAR signal, which refers to the orientation of the electric field emitted and received by the SAR sensor in the vertical (V) or horizontal (H) axis, and can be co-polarized (VV and HH -emitted and received vertically or horizontally, respectively), or cross-polarized (VH, and HV -emitted in one orientation and received in another), will have a great effect on the signal backscattered by vegetation (SOUZA et al, 2019). When additional information from backscattering phase is available, the magnitude of the polarimetric response makes possible the characterization of the objects scattering mechanisms as well (GARCIA et al, 2012).…”
Section: Introductionmentioning
confidence: 99%