For many years, spectral remote sensing has been essential for research on the Earth's
surface. The data from a single satellite sensor is sometimes insufficient to fulfil the …

To reduce human losses and minimize social and economic disruption caused by large-
scale earthquakes, effective planning and operational decisions need to be made by …

Quick building damage assessment following disasters such as large earthquakes serves to
establish a preliminary estimation of losses and casualties. These datasets are completed …

Post-disaster analysis poses a significant challenge in Disaster Risk Management during
the recovery phase. This study explores the advantages of multispectral images from …

Abstract Dst (Disturbance Storm Time) is an hourly index of magnetic activity computed from
the measured intensity of the globally symmetrical equatorial electrojet (Ring Current) …

Building damage assessment with remote sensing images plays an important role in
providing information for disaster rescue and reconstruction. Recently, deep convolutional …

Since 1980, millions of people have been harmed by natural disasters that have cost society
over three trillion dollars. After a natural disaster has occurred, the creation of maps that …

In this study, we have analysed the optical and SAR images both to detect the collapsed
building automatically with the use of the cloud-based programming environment Google …

Recently, a need has arisen for prediction techniques that can address a variety of problems
by combining methods from the rapidly developing field of machine learning with …

Developing strategies to mitigate damage from high-risk buildings in earthquake-prone
areas is essential. This study focuses on prioritizing buildings based on their risk levels …