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Quick response to a large-scale natural disaster such as earthquake and tsunami is vital to mitigate the further loss. Remote sensing especially the spaceborne sensors provide the solution to monitor a huge area in a short time and with regular revisit circle. Damage ranges and damage levels of the destructed urban areas are extremely important information for rescue planning after an event. Rapid...
Mapping of the urban damage levels with synthetic aperture radar (SAR) is still challenging. Fully polarimetric SAR (PolSAR) has the potential to identify the type of scattering mechanism changes induced by urban damage. In radar polarimetry, dominant double-bounce scattering mechanism in urban areas is primarily induced by the ground-wall structures. Thereby, within an urban patch, the reduction...
This paper focuses on earthquake/tsunami damage investigation over urban areas by exploring the multitemporal spaceborne ALOS/PALSAR PolSAR data. The polarimetric scattering mechanism changes before- and after-tsunami, at the city block scale, have been examined using model-based decomposition and PO angle techniques. These analyzes are used to establish the relationships between the polarimetric...
An optimized architecture is proposed for real-time automatic cloud detection system with Spectrum and Texture Analysis Combination (STAC) approach. The STAC approach is hard to be implemented in hardware, for the calculation of fractal dimension (FD) and angle second moments (ASM) of the approach consumes large computation time and hardware resources. By optimizing the calculation process of the...
The remote sensing images often encounter the problem of cloud cover, and this may obstruct the use of certain image data. So a cloud detecting process is required to mask out the cloudy pixels. With the trend of satellite missions towards lower cost and wide coverage, the demand of on-board processing becomes more insistent. Reconfigurable logic devices combining the flexibility of software-based...
Multispectral images provide detailed data with information in both the spatial and spectral domains. Many clustering methods for multispectral images are based on a per-pixel classification, while uses only spectral information and ignores spatial information. In this work, a new clustering algorithm for multispectral images, based on both spectral and spatial information, is presented. This algorithm...
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