Improving flood damage assessments in data-scarce areas by retrieval of building characteristics through UAV image segmentation and machine learning – a case study of the 2019 floods in southern Malawi
Lucas Wouters et al.
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Total article views: 964 (including HTML, PDF, and XML)
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776
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964
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Total article views: 984 (including HTML, PDF, and XML)
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635
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HTML: 635
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Total article views: 1,825 (including HTML, PDF, and XML)
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Total article views: 911 (including HTML, PDF, and XML)
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Total article views: 914 (including HTML, PDF, and XML)
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This research introduces a novel approach to estimate flood damage in Malawi by applying a machine learning model to UAV imagery. We think that the development of such a model is an essential step to enable the swift allocation of resources for recovery by humanitarian decision-makers. By comparing this method (EUR 10 140) to a conventional land-use-based approach (EUR 15 782) for a specific flood event, recommendations are made for future assessments.
This research introduces a novel approach to estimate flood damage in Malawi by applying a...
