کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6346233 1621242 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Mapping the 2010 Merapi pyroclastic deposits using dual-polarization Synthetic Aperture Radar (SAR) data
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
پیش نمایش صفحه اول مقاله
Mapping the 2010 Merapi pyroclastic deposits using dual-polarization Synthetic Aperture Radar (SAR) data
چکیده انگلیسی


- We characterize pyroclastic deposits using co- and cross-polarized L-band SAR data.
- We use L-band ALOS-PALSAR images to classify the 2010 Merapi pyroclastic deposits.
- Changes in radar amplitude efficiently enable us to map the pyroclastic deposits.
- Maximum likelihood classification helps to map 4 main pyroclastic deposit units.
- Temporal decorrelation information has improved the classification results.

L-band ALOS-PALSAR images acquired before, during and after the 2010 Merapi eruption have been used to classify and map the pyroclastic deposits emplaced during this VEI-4 event. We characterize the deposits using direct-polarized and cross-polarized L-band SAR data and by combining the information of amplitude evolution with temporal decorrelation. Changes in amplitude of the radar signal enable us to map the pyroclastic density currents (PDCs) and tephra-fall deposits. Radar amplitudes in direct (HH) and cross (HV) polarizations decrease where the valley-confined and overbank block-and-ash flow (BAF) deposits (D1) are emplaced. Rainfall- and runoff-reworked PDC deposits (D2) are characterized by an increase in ground backscattering for HH polarization and a decrease for HV polarization. Ground backscattering transiently increases in both polarizations after pyroclastic surge (D3) and tephra fall (D4) deposition. We use a supervised classification method based on maximum likelihood to map the deposits D1-D4. The temporal decorrelation of the radar signal and the amplitude evolution improve the quality of classification results. Classification derived from ALOS-PALSAR images using the maximum likelihood classification provides a result with 70% classification accuracy for deposits overall. The estimated areas of valley-confined and overbank PDC deposits (either primary or reworked by rainfall and runoff) are consistent with the areas measured by other studies, while the large discrepancy in area estimated for pyroclastic-surge deposits can be partly explained by the strong erosion due to intense rainfall that removed a large part of these thin deposits.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 158, 1 March 2015, Pages 180-192
نویسندگان
, , , , ,