Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …

In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …

Unplanned urban settlements exist worldwide. The geospatial information of these areas is
critical for urban management and reconstruction planning but usually unavailable …

Automatic extraction of building footprints from high-resolution satellite imagery has become
an important and challenging research issue receiving greater attention. Many recent …

Efficient and accurate building damage assessment is crucial for effective emergency
response and resource allocation following natural hazards. However, traditional methods …

Post-disaster damage map** is an essential task following tragic events such as
hurricanes, earthquakes, and tsunamis. It is also a time-consuming and risky task that still …

Identifying permanent water and temporary water in flood disasters efficiently has mainly
relied on change detection method from multi-temporal remote sensing imageries, but …

Due to the unique advantages of microwave detection, such as its low restriction from the
atmosphere and its capability to obtain structural information about ground targets, synthetic …

There has been an unsettling rise in the intensity and frequency of natural disasters due to
climate change and anthropogenic activities. Artificial intelligence (AI) models have shown …

Emergency situations encompassing natural and human-made disasters, as well as their
cascading effects, pose serious threats to society at large. Machine learning (ML) algorithms …