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Urban change detection is an important part of monitoring operations and disaster relief efforts. However, often sufficient ground truth data is not available to use traditional supervised machine learning techniques. In this paper, a novel Deep Learning based weakly-supervised framework for urban change detection using multi-temporal polarimetric SAR data is proposed. A modified unsupervised stacked...
Synthetic aperture radar (SAR) has shown promising results in characterizing different crops. Multi-temporal SAR data is often useful for studying the sensitivity of the electromagnetic (EM) waves to the structural and the dielectric variation of both crops and the underlying soil at different phenological stages. Physical information about crops and soil can be interpreted in terms of scattering...
Extraction of polarimetric information from SAR data is one of the most important issues in SAR applications. Since fully polarimetric SAR data and model-based scattering power decomposition are now available, its real utilization becomes important topic. In this presentation, some data sets from PiSAR-L2, ALOS, ALOS-2 systems are shown using the existing model-based scattering power decompositions...
Cryosphere plays a crucial role in regulating local and global climate. Glaciers form an important component of this frozen part of the Earth's system. They exist over a prolonged period and are largest reservoir of freshwater on Earth. The meltwater from the glaciers during warmer seasons contribute to the river systems in absence of other sources. The run-off is also useful for agriculture, power...
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