3-D mapping shows flood damage based on SNS posts
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A Tokyo-based IT company developed a 3-D mapping system to reproduce data on flooding in stricken areas in almost real time based on images posted on social media.
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The technology is aimed at helping rescue services and residents quickly grasp the extent of inundation in local areas.
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“It (the map system) will lead to faster development of disaster management plans by municipalities and companies,” said a representative of Spectee Inc., which used artificial intelligence (AI) to develop the system.
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Based on image analysis using AI, the firm automatically judged road surface conditions and detected and predicted river flooding.
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For its latest project, Spectee referred to widespread inundation around the Kumagawa river in Kumamoto Prefecture during torrential rains in July last year as a model case.
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It analyzed the situation by combining photos uploaded to social networking sites with rainfall data, map information and past flooding records.
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That allowed it to recreate the areas and depth of flooding on a 3-D map within 10 to 15 minutes, according to Spectee.
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Analysis of a single image allows the company to estimate inundation levels for a 10-square-kilometer area.
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When massive flooding occurs, it is often difficult to grasp the severity of the situation in affected zones, adding to the time it takes to start recovery efforts from the disaster.
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The 3-D mapping technology promises to produce fast results on flood damage, thereby allowing local authorities and businesses to figure out what to do and where to accommodate evacuees during such emergencies.
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“We plan to further improve the system to gauge inundation levels and other factors when natural disasters hit in the future,” said a Spectee representative.
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