{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T11:28:49Z","timestamp":1779276529850,"version":"3.51.4"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319939308","type":"print"},{"value":"9783319939315","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-93931-5_25","type":"book-chapter","created":{"date-parts":[[2018,6,15]],"date-time":"2018-06-15T07:25:18Z","timestamp":1529047518000},"page":"347-358","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Satellite Imagery Analysis for Operational Damage Assessment in Emergency Situations"],"prefix":"10.1007","author":[{"given":"German","family":"Novikov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexey","family":"Trekin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Georgy","family":"Potapov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vladimir","family":"Ignatiev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evgeny","family":"Burnaev","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,6,16]]},"reference":[{"key":"25_CR1","unstructured":"About the Disasters Charter. International Disasters Charter. 2000\u20132018. https:\/\/disasterscharter.org\/web\/guest\/about-the-charter"},{"key":"25_CR2","unstructured":"Eguchi, R.T., et al.: The January 12, 2010 Haiti earthquake: a comprehensive damage assessment using very high resolution areal imagery. In: 8th International Workshop on Remote Sensing for Disaster Management. Tokyo Institute of Technology, Japan (2010)"},{"key":"25_CR3","unstructured":"About \u2013 Humanitarian OpenStreetMap Team. https:\/\/www.hotosm.org\/about"},{"key":"25_CR4","unstructured":"Maps and Data \u2013 UNITAR. http:\/\/www.unitar.org\/unosat\/maps"},{"key":"25_CR5","unstructured":"Tomnod (2018). https:\/\/www.tomnod.com\/"},{"key":"25_CR6","unstructured":"OpenStreetMap\/iD: The easy-to-use OpenStreetMap editor in JavaScript (2018). https:\/\/github.com\/openstreetmap\/iD"},{"key":"25_CR7","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/978-1-4614-8806-4_11","volume-title":"Handbook of Human Computation","author":"P Meier","year":"2013","unstructured":"Meier, P.: Human computation for disaster response. In: Michelucci, P. (ed.) Handbook of Human Computation, pp. 95\u2013104. Springer, New York (2013). https:\/\/doi.org\/10.1007\/978-1-4614-8806-4_11"},{"key":"25_CR8","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1553\/giscience2017_01_s157","volume":"1","author":"Stefan Lang","year":"2017","unstructured":"Lang, S., et al.: Earth Observation for Humanitarian Assistance GI Forum 2017, vol. 1, pp. 157\u2013165 (2017)","journal-title":"GI_Forum"},{"key":"25_CR9","doi-asserted-by":"crossref","unstructured":"Dittus M., Quattrone G., Capra L.: Mass participation during emergency response: event-centric crowdsourcing in humanitarian mapping. In: CSCW, 2017, pp. 1290\u20131303 (2017)","DOI":"10.1145\/2998181.2998216"},{"issue":"6","key":"25_CR10","doi-asserted-by":"publisher","first-page":"1520","DOI":"10.1109\/TGRS.2007.895830","volume":"45","author":"S Voigt","year":"2007","unstructured":"Voigt, S., Kemper, T., Riedlinger, T., Kiefl, R., Scholte, K., Mehl, H.: Satellite image analysis for disaster and crisis-management support. IEEE Trans. Geosci. Remote Sens. 45(6), 1520\u20131528 (2007)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"25_CR11","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1177\/0309133309339563","volume":"33","author":"KE Joyce","year":"2009","unstructured":"Joyce, K.E., Belliss, S.E., et al.: A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters. Progress Phys. Geogr. 33(2), 183\u2013207 (2009)","journal-title":"Progress Phys. Geogr."},{"issue":"6","key":"25_CR12","doi-asserted-by":"publisher","first-page":"1631","DOI":"10.1109\/TGRS.2007.890808","volume":"45","author":"CF Barnes","year":"2007","unstructured":"Barnes, C.F., Fritz, H., Yoo, J.: Hurricane disaster assessments with image-driven data mining in high-resolution satellite imagery. IEEE Trans. Geosci. Remote Sens. 45(6), 1631\u20131640 (2007)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"25_CR13","unstructured":"Open Data Program - DigitalGlobe (2018). https:\/\/www.digitalglobe.com\/opendata"},{"key":"25_CR14","unstructured":"http:\/\/www.fire.ca.gov\/communications\/downloads\/fact_sheets\/Top20_Destruction.pdf"},{"key":"25_CR15","unstructured":"Before and after: Where the Thomas fire destroyed buildings in Ventura (analysis made by The Los Angeles Times using sat. imagery by Digitalglobe). http:\/\/www.latimes.com\/projects\/la-me-socal-fires-destroyed-structures\/"},{"key":"25_CR16","unstructured":"Chollet, F.: Keras (2015)"},{"key":"25_CR17","unstructured":"Ronneberger, O., et al.: U-Net: convolutional networks for biomedical image segmentation. https:\/\/arxiv.org\/abs\/1505.04597"},{"key":"25_CR18","unstructured":"Abadi, M., Barham, P., Chen, J., et el.: TensorFlow: a system for large-scale machine learning. In: OSDI, vol. 16, pp. 265\u2013283"},{"key":"25_CR19","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L. J., Li, K., Fei-Fei, L.: ImageNet: a large-scale hierarchical image database. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 248\u2013255 (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"25_CR20","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3431\u20133440 (2015)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"25_CR21","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Advances in Neural Information Processing Systems, pp. 1097\u20131105 (2012)"},{"key":"25_CR22","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Dollar, P., Girshick, R.: Mask R-CNN. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2980\u20132988. IEEE, October 2017","DOI":"10.1109\/ICCV.2017.322"},{"key":"25_CR23","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)"},{"key":"25_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1007\/978-3-319-73013-4_23","volume-title":"Analysis of Images, Social Networks and Texts","author":"A Notchenko","year":"2018","unstructured":"Notchenko, A., Kapushev, Y., Burnaev, E.: Large-scale shape retrieval with sparse 3D convolutional neural networks. In: van der Aalst, W.M.P., et al. (eds.) AIST 2017. LNCS, vol. 10716, pp. 245\u2013254. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-73013-4_23"},{"key":"25_CR25","doi-asserted-by":"crossref","unstructured":"Burnaev, E., Koptelov, I., Novikov, G., Khanipov, T.: Automatic construction of a recurrent neural network based classifier for vehicle passage detection. In: Proceedings of SPIE, 9th International Conference on Machine Vision (ICMV 2016), vol. 10341, p. 1034103 (2016)","DOI":"10.1117\/12.2268706"},{"key":"25_CR26","doi-asserted-by":"crossref","unstructured":"Artemov, A., Burnaev, E.: Ensembles of detectors for online detection of transient changes. In: Proceedings of SPIE, Eighth International Conference on Machine Vision, vol. 9875, p. 98751Z:5 (2015)","DOI":"10.1117\/12.2228369"},{"key":"25_CR27","unstructured":"Volkhonsky, D., Burnaev, E., Nouretdinov, I., Gammerman, A., Vovk, V.: Inductive conformal martingales for change-point detection. In: The 6th Symposium on Conformal and Probabilistic Prediction with Applications (COPA) 2017, Proceedings of Machine Learning Research, vol. 60, pp. 132\u2013153 (2017)"},{"key":"25_CR28","first-page":"23","volume":"3","author":"A Safin","year":"2017","unstructured":"Safin, A., Burnaev, E.: Conformal kernel expected similarity for anomaly detection in time-series data. Adv. Syst. Sci. Appl. 3, 23\u201334 (2017)","journal-title":"Adv. Syst. Sci. Appl."}],"container-title":["Lecture Notes in Business Information Processing","Business Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-93931-5_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T11:24:50Z","timestamp":1710242690000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-93931-5_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319939308","9783319939315"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-93931-5_25","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"value":"1865-1348","type":"print"},{"value":"1865-1356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"16 June 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Business Information Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Berlin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 July 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 July 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bis2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/bis.ue.poznan.pl\/bis2018\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"96","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"30","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"31% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.375","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4.83","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}