Big data in natural disaster management: a review
Undoubtedly, the age of big data has opened new options for natural disaster management,
primarily because of the varied possibilities it provides in visualizing, analyzing, and …
primarily because of the varied possibilities it provides in visualizing, analyzing, and …
A comprehensive review of earthquake-induced building damage detection with remote sensing techniques
L Dong, J Shan - ISPRS Journal of Photogrammetry and Remote …, 2013 - Elsevier
Earthquakes are among the most catastrophic natural disasters to affect mankind. One of the
critical problems after an earthquake is building damage assessment. The area, amount …
critical problems after an earthquake is building damage assessment. The area, amount …
Early detection of earthquakes using iot and cloud infrastructure: A survey
Earthquake early warning systems (EEWS) are crucial for saving lives in earthquake-prone
areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a …
areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a …
UAV-based structural damage map**: A review
Structural disaster damage detection and characterization is one of the oldest remote
sensing challenges, and the utility of virtually every type of active and passive sensor …
sensing challenges, and the utility of virtually every type of active and passive sensor …
Building damage detection using U-Net with attention mechanism from pre-and post-disaster remote sensing datasets
The building damage status is vital to plan rescue and reconstruction after a disaster and is
also hard to detect and judge its level. Most existing studies focus on binary classification …
also hard to detect and judge its level. Most existing studies focus on binary classification …
UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning
J Fernandez Galarreta, N Kerle… - Natural hazards and …, 2015 - nhess.copernicus.org
Structural damage assessment is critical after disasters but remains a challenge. Many
studies have explored the potential of remote sensing data, but limitations of vertical data …
studies have explored the potential of remote sensing data, but limitations of vertical data …
Combining human computing and machine learning to make sense of big (aerial) data for disaster response
Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly
important role in disaster response. Unlike satellite imagery, aerial imagery can be captured …
important role in disaster response. Unlike satellite imagery, aerial imagery can be captured …
Predicting road blockage due to building damage following earthquakes
Transportation infrastructure supports the social and economic activities of communities.
One of the impacts of roads' disruption is the obstruction of emergency services (eg …
One of the impacts of roads' disruption is the obstruction of emergency services (eg …
Identifying collapsed buildings using post-earthquake satellite imagery and convolutional neural networks: A case study of the 2010 Haiti earthquake
Earthquake is one of the most devastating natural disasters that threaten human life. It is vital
to retrieve the building damage status for planning rescue and reconstruction after an …
to retrieve the building damage status for planning rescue and reconstruction after an …
Automatic building extraction from Google Earth images under complex backgrounds based on deep instance segmentation network
Building damage accounts for a high percentage of post-natural disaster assessment.
Extracting buildings from optical remote sensing images is of great significance for natural …
Extracting buildings from optical remote sensing images is of great significance for natural …