Zobrazeno 1 - 10
of 120
pro vyhledávání: '"Building damage detection"'
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTRapidly estimating post-disaster building damage via high-resolution remote sensing (HRRS) imagery is essential for initial disaster relief. However, the complex appearance of building damage poses challenges for existing methods. Specificall
Externí odkaz:
https://doaj.org/article/d0e5a7e492604600ae4a9926b69d2da5
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 15301-15318 (2024)
Building collapse is a leading cause of casualties and economic losses during disasters. Accurate and timely assessment of building damage is critical for effective emergency response and recovery efforts. This article provides a comprehensive review
Externí odkaz:
https://doaj.org/article/f477f282573b4bef92c82e2cc08b6888
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14109-14121 (2024)
The statistics of damaged buildings after natural disasters are crucial for rescue operations, especially for damaged buildings that are extremely challenging for object detection. There are unique spatial distribution problems in the existing damage
Externí odkaz:
https://doaj.org/article/94ba0b3c7856436293f7dcafb2ed2317
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13120-13134 (2024)
Natural disasters commonly occur in all regions around the world and cause huge financial and human losses. One of the main effects of earthquakes and floods is the destruction of buildings. Photogrammetric and remote sensing (RS) data track changes
Externí odkaz:
https://doaj.org/article/30f47286353442d491108d40ac6b2ba0
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1046-1059 (2024)
Synthetic aperture radar (SAR) imagery is indispensable for acquiring a comprehensive, large-scale topographical perspective of the Earth's surface, facilitating the evaluation of diverse scenarios spanning various events. However, integrating SAR im
Externí odkaz:
https://doaj.org/article/2586ed6f2abd4a18b4365c0f6563f412
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 5651-5667 (2024)
Integrated with remote sensing technology, deep learning has been increasingly used for rapid damage assessment. Despite reportedly having high accuracy, the approach requires numerous samples to maintain its performance. However, in the emergency re
Externí odkaz:
https://doaj.org/article/ba41ad06aa6d461680b7bf582672bfe3
Autor:
Riantini Virtriana, Agung Budi Harto, Fiza Wira Atmaja, Irwan Meilano, Kamal Nur Fauzan, Tania Septi Anggraini, Kalingga Titon Nur Ihsan, Fatwa Cahya Mustika, Wulan Suminar
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 14, Iss 1, Pp 28-51 (2023)
AbstractIn 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 Sunda Strait due to the eruption of the Anak Krakatau Vol
Externí odkaz:
https://doaj.org/article/c17e42ed001443dc9407f695d5469811
Autor:
Burak Tasci, Madhav R. Acharya, Mehmet Baygin, Sengul Dogan, Turker Tuncer, Samir Brahim Belhaouari
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 123, Iss , Pp 103483- (2023)
In February 2023, Turkey experienced a series of earthquakes that caused significant damage to buildings and affected many people. Detecting building damage quickly is crucial for helping earthquake victims, and we believe machine learning models off
Externí odkaz:
https://doaj.org/article/3651cf2dd6ed4d0f975f402698410b0b
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