2012
DOI: 10.1109/lgrs.2011.2174611
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Applying Bayesian Decision Classification to Pi-SAR Polarimetric Data for Detailed Extraction of the Geomorphologic and Structural Features of an Active Volcano

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Cited by 23 publications
(15 citation statements)
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“…The accuracy of the D-InSAR approach has been widely proved in previous studies of precise movement extraction [20,22]. According to the D-InSAR result, the accuracy of the PT method can also be ensured because of the existing overlapping region.…”
Section: Accuracy Estimation and Error Analysismentioning
confidence: 96%
“…The accuracy of the D-InSAR approach has been widely proved in previous studies of precise movement extraction [20,22]. According to the D-InSAR result, the accuracy of the PT method can also be ensured because of the existing overlapping region.…”
Section: Accuracy Estimation and Error Analysismentioning
confidence: 96%
“…One of the monitoring was done by studying the rocks of the ancient volcanic products including identifying type and distribution of rocks. Surface volcanic rocks identification in active volcano is crucial not only to mitigate volcanic hazards, but also to characterize eruption, urban rehabilitation, and reconstruction especially after eruption [3].…”
Section: Introductionmentioning
confidence: 99%
“…Therefore, the field observation requires a lot of time and cost. Utilization of [3]. The change of volcanic rocks in one composite volcano might reflect the occurrence of magmatic evolution presented by variation in petrology and geochemistry of the rocks.…”
Section: Introductionmentioning
confidence: 99%
“…While decomposition techniques have been widely used in the environmental field to classify polarimetric radar data of target surface scattering, its application to geosciences is still rare [3]. Saepuloh et al (2012) [4] used the polarimetric decomposition techniques of Cloude and Poittier to extract the geomorphology and structure of active volcanoes by using surface roughness at the volcanoes. From the surface roughness they were able to distinguish between surface alterations, hot mud, and hot springs.…”
Section: Introductionmentioning
confidence: 99%