The level of destruction caused by an earthquake depends on a variety of factors, such as
magnitude, duration, intensity, time of occurrence, and underlying geological features, which …

Soil liquefaction often occurs as a secondary hazard during earthquakes and can lead to
significant structural and infrastructure damage. Liquefaction is most often documented …

Deep learning-based frameworks have not been much explored to incorporate the temporal
dimension of the remote sensing data. In this research work, deep learning-based models …

The research study proposes a fuzzy machine learning based approach for the detection of
transitioning building footprints in urban area using temporal high and medium resolution …

On 15 November 2017, liquefaction phenomena were observed around the epicenter after a
5.4 magnitude earthquake occurred in Pohang in southeast Korea. In this study, we …

In remote sensing images, pixel-based classifiers use means or variance-covariance
statistical parameters generated from training sample data sets. These parameters do not …

Paddy transplantation rate mapping can provide important information regarding water
demand for its transplantation. It is a time-tagged activity that cannot be accurately mapped …

Infrastructures damage detection in case of major disasters is one of the most discussed
problems and represent an active field of research in remotely sensed imaging. In this …

Rapid extraction of liquefaction induced by strong earthquakes is helpful for earthquake
intensity assessment and earthquake emergency response. Supervised classification …

With increasing availability of satellite data of high temporal resolution, a more robust
classifier is needed which can exploit the temporal information along with the spectral …