Satellite imagery analysis for operational damage assessment in Emergency situations
When major disaster occurs the questions are raised how to estimate the damage in time to support the decision making process and relief efforts by local authorities or humanitarian teams. In this paper we consider the use of Machine Learning and Computer Vision on remote sensing imagery to improve...
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| Veröffentlicht in: | arXiv.org 2018-02 |
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| creator | Trekin, Alexey Novikov, German Potapov, Georgy Ignatiev, Vladimir Burnaev, Evgeny |
| description | When major disaster occurs the questions are raised how to estimate the damage in time to support the decision making process and relief efforts by local authorities or humanitarian teams. In this paper we consider the use of Machine Learning and Computer Vision on remote sensing imagery to improve time efficiency of assessment of damaged buildings in disaster affected area. We propose a general workflow that can be useful in various disaster management applications, and demonstrate the use of the proposed workflow for the assessment of the damage caused by the wildfires in California in 2017. |
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| language | eng |
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| source | Free E- Journals |
| subjects | Computer vision Damage assessment Decision making Disaster management Emergency procedures Forest & brush fires Machine learning Remote sensing Satellite imagery Wildfires Workflow |
| title | Satellite imagery analysis for operational damage assessment in Emergency situations |
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