A survey on deep learning-based change detection from high-resolution remote sensing images
H Jiang, M Peng, Y Zhong, H Xie, Z Hao, J Lin, X Ma… - Remote Sensing, 2022 - mdpi.com
Change detection based on remote sensing images plays an important role in the field of
remote sensing analysis, and it has been widely used in many areas, such as resources …
remote sensing analysis, and it has been widely used in many areas, such as resources …
Tsunami damage detection with remote sensing: A review
Tsunamis are rare events compared with the other natural disasters, but once it happens, it
can be extremely devastating to the coastal communities. Extensive inland penetration of …
can be extremely devastating to the coastal communities. Extensive inland penetration of …
Graph-based block-level urban change detection using Sentinel-2 time series
Remote sensing technology has been frequently used to obtain information on changes in
urban land cover because of its vast spatial coverage and timeliness of observation. Block …
urban land cover because of its vast spatial coverage and timeliness of observation. Block …
Temporal-agnostic change region proposal for semantic change detection
Remote sensing imagery allows temporal and large-scale observation of the Earth, and
advanced techniques such as deep learning have been developed to deal with the massive …
advanced techniques such as deep learning have been developed to deal with the massive …
War related building damage assessment in Kyiv, Ukraine, using Sentinel-1 radar and Sentinel-2 optical images
Natural and anthropogenic disasters can cause significant damage to urban infrastructure,
landscape, and loss of human life. Satellite based remote sensing plays a key role in rapid …
landscape, and loss of human life. Satellite based remote sensing plays a key role in rapid …
Model-based analysis of multi-UAV path planning for surveying postdisaster building damage
Emergency responders require accurate and comprehensive data to make informed
decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient …
decisions. Moreover, the data should be acquired and analyzed swiftly to ensure an efficient …
Machine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami
In Indonesia, tsunamis are frequent events. In 2000–2016, there were 44 tsunami events in
Indonesia, with financial losses reaching 43.38 trillion. In 2018, a tsunami occurred in the …
Indonesia, with financial losses reaching 43.38 trillion. In 2018, a tsunami occurred in the …
Earthquake-induced building-damage mapping using Explainable AI (XAI)
SS Matin, B Pradhan - Sensors, 2021 - mdpi.com
Building-damage mapping using remote sensing images plays a critical role in providing
quick and accurate information for the first responders after major earthquakes. In recent …
quick and accurate information for the first responders after major earthquakes. In recent …
Seismic risk regularization for urban changes due to earthquakes: A case of study of the 2023 turkey earthquake sequence
A Portillo, L Moya - Remote Sensing, 2023 - mdpi.com
Damage identification soon after a large-magnitude earthquake is a major problem for early
disaster response activities. The faster the damaged areas are identified, the higher the …
disaster response activities. The faster the damaged areas are identified, the higher the …
Beyond tsunami fragility functions: experimental assessment for building damage estimation
Tsunami fragility functions (TFF) are statistical models that relate a tsunami intensity
measure to a given building damage state, expressed as cumulative probability. Advances …
measure to a given building damage state, expressed as cumulative probability. Advances …