{"id":920430,"date":"2023-02-16T15:12:15","date_gmt":"2023-02-16T23:12:15","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2023-02-17T08:06:18","modified_gmt":"2023-02-17T16:06:18","slug":"turkey-earthquake-report","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/turkey-earthquake-report\/","title":{"rendered":"Turkey Earthquake Report"},"content":{"rendered":"

After the earthquake in Turkey on February 6th, our team <\/span><\/span>began to utilize artificial intelligence (AI) methods and <\/span><\/span>high-resolution satellite imagery to assess the extent of <\/span><\/span>damage to buildings in the affected region. Specifically, <\/span><\/span>we partnered with Turkey\u2019s Ministry of Interior Disaster <\/span><\/span>and Emergency Management Presidency (AFAD) to <\/span><\/span>deliver building level damage estimates over four cities <\/span><\/span>in southeast Turkey using satellite imagery from the first <\/span><\/span>3 days of the disaster. We estimate 3,849 buildings were <\/span><\/span>damaged\/destroyed across the four cities. We found the <\/span><\/span>city of Marash* to be the most heavily affected, with 7.44% <\/span><\/span>of buildings in the city sustaining some level of damage <\/span><\/span>visible from satellite imagery.<\/span><\/span><\/p>\n

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After the earthquake in Turkey on February 6th, our team began to utilize artificial intelligence (AI) methods and high-resolution satellite imagery to assess the extent of damage to buildings in the affected region. Specifically, we partnered with Turkey\u2019s Ministry of Interior Disaster and Emergency Management Presidency (AFAD) to deliver building level damage estimates over four […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,198583],"msr-publication-type":[193718],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-920430","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-ecology-environment","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2023-2-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"MSR-TR-2023-7","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"Microsoft","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/02\/Turkey-Earthquake-Report-2_MS.pdf","id":"920463","title":"turkey-earthquake-report-2_ms","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":920463,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/02\/Turkey-Earthquake-Report-2_MS.pdf"},{"id":920448,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2023\/02\/Turkey-Earthquake-Report_MS.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Caleb Robinson","user_id":39606,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Caleb Robinson"},{"type":"text","value":"Ritwik Gupta","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Simone Fobi Nsutezo","user_id":41988,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Simone Fobi Nsutezo"},{"type":"text","value":"Erick Pound","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Anthony Ortiz","user_id":39715,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Anthony Ortiz"},{"type":"text","value":"Melissa Rosa","user_id":0,"rest_url":false},{"type":"guest","value":"kevin-white","user_id":898320,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=kevin-white"},{"type":"user_nicename","value":"Rahul Dodhia","user_id":41401,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Rahul Dodhia"},{"type":"text","value":"Andrew Zolli","user_id":0,"rest_url":false},{"type":"guest","value":"cameron-birge","user_id":778015,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=cameron-birge"},{"type":"user_nicename","value":"Juan M. 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