Corbane, C., Saito, K., Dell'Oro, L., Bjorgo, E., Gill, S. P. D., Piard, B. E., Huyck, C. K., Kemper, T., Lemoine, G., Spence, R. J. S., Shankar, R., Senegas, O., Ghesquiere, F., Lallemant, D., Evans, G. B., Gartley, R. A., Toro, J., Ghosh, S., Svekla, W. D., Adams, B. J., and Eguchi, R. T.: A comprehensive analysis of building damage in the 12 January 2010 MW7 Haiti earthquake using high-resolution satelliteand aerial imagery, Photogram. Eng. Remote Sens., 77, 997–1009, 2011.
Dell'Acqua, F. and Gamba, P.: Remote sensing and earthquake damage assessment: experiences, limits, and perspectives, Proc. IEEE, 100, 2876–2890, https://doi.org/10.1109/jproc.2012.2196404, 2012.
Drăguţ, L., Csillik, O., Eisank, C., and Tiede, D.: Automated parameterisation for multi-scale image segmentation on multiple layers, ISPRS J. Photogram. Remote Sens., 88, 119–127, https://doi.org/10.1016/j.isprsjprs.2013.11.018, 2014.
eCognition: A development environment for object-based image analysis, http://www.ecognition.com/, last access: 19 August 2013.
Ehrlich, D., Guo, H. D., Molch, K., Ma, J. W., and Pesaresi, M.: Identifying damage caused by the 2008 Wenchuan earthquake from VHR remote sensing data, Int. J. Digit. Earth, 2, 309–326, https://doi.org/10.1080/17538940902767401, 2009.
Fernandez Galarreta, J.: MSc thesis: Urban structural damage assessment using object – oriented analysis and semantic reasoning, University of Twente, Faculty of Geo-Information and Earth Observation (ITC), Enschede, 93 pp., 2014.
Furukawa, Y. and Ponce, J.: Accurate, dense, and robust multiview stereopsis, IEEE T. Pattern Anal. Mach. Intell., 32, 1362–1376, https://doi.org/10.1109/tpami.2009.161, 2010.
Gerke, M. and Kerle, N.: Automatic structural seismic damage assessment with airborne oblique pictometry (c) imagery, Photogram. Eng. Remote Sens., 77, 885–898, 2011a.
Gerke, M. and Kerle, N.: Graph matching in 3D space for structural seismic damage assessment, IEEE International Conference on Computer Vision Workshops (ICCV Workshops), Barcelona, 204–211, 2011b.
Grünthal, G.: European Macroseismic Scale 1998 (EMS-98), Cahiers du Centre Européen de Géodynamique et de Séismologie, Centre Européen de Géodynamique et de Séismologie, Luxembourg, 1998.
Johnson, B. and Xie, Z.: Unsupervised image segmentation evaluation and refinement using a multi-scale approach, ISPRS J. Photogram. Remote Sens., 66, 473–483, https://doi.org/10.1016/j.isprsjprs.2011.02.006, 2011.
Joshi, J. R.: Improving the quality of digital surface model generated from very high resolution satellite stereo imagery by using object oriented image analysis technique, University of Twente Faculty of Geo-Information and Earth Observation (ITC), Enschede, 106 pp., 2010.
Kerle, N.: Satellite-based damage mapping following the 2006 Indonesia earthquake – How accurate was it?, Int. J. Appl. Earth Observ. Geoinf., 12, 466-476, https://doi.org/10.1016/j.jag.2010.07.004, 2010.
Kerle, N. and Hoffman, R. R.: Collaborative damage mapping for emergency response: the role of Cognitive Systems Engineering, Nat. Hazards Earth Syst. Sci., 13, 97–113, https://doi.org/10.5194/nhess-13-97-2013, 2013.
Kerle, N., Heuel, S., and Pfeifer, N.: Real-time data collection and information generation using airborne sensors, Geospatial Information Technology for Emergency Response, edited by: Zlatanova, S. A. L., Taylor &,Francis, London, 43–74, 2008.
Khoshelham, K., Oude Elberink, S., and Sudan, X.: Segment-based classification of damaged building roofs in aerial laser scanning data, IEEE Geosci. Remote Sens. Lett., 10, 1258–1262, https://doi.org/10.1109/lgrs.2013.2257676, 2013.
Li, P. J., Xu, H. Q., and Guo, J. C.: Urban building damage detection from very high resolution imagery using OCSVM and spatial features, Int. J. Remote Sens., 31, 3393–3409, https://doi.org/10.1080/01431161003727705, 2010.
Lu, P., Stumpf, A., Kerle, N., and Casagli, N.: Object-oriented change detection for landslide rapid mapping, IEEE Geosci. Remote Sens. Lett., 8, 701–705, https://doi.org/10.1109/lgrs.2010.2101045, 2011.
Martha, T. R., Kerle, N., van Westen, C. J., Jetten, V., and Kumar, K. V.: Segment optimization and data-driven thresholding for knowledge-based landslide detection by object-based image analysis, IEEE T. Geosci. Remote, 49, 4928–4943, https://doi.org/10.1109/tgrs.2011.2151866, 2011.
Mitomi, H., Saita, J., Matsuoka, M., and Yamazaki, F.: Automated damage detection of buildings from aerial television images of the 2001 Gujarat, India earthquake, IEEE 2001 International Geoscience and Remote Sensing Symposium, IGARSS '01, Sydney, 147–149, 2001.
Musialski, P., Wonka, P., Aliaga, D. G., Wimmer, M., van Gool, L., and Purgathofer, W.: A survey of urban reconstruction, Comput. Graph. Forum, 32, 146–177, https://doi.org/10.1111/cgf.12077, 2013.
Nonami, K., Kendoul, F., Suzuki, S., Wang, W., and Daisuke, N.: Autonomous flying robots, Springer Verlag, Tokio, 2010.
Oude Elberink, S. J., Shoko, M., Fathi, S. A. M., and Rutzinger, M.: Detection of collapsed buildings by classifying segmented airborne laser scanner data, in: ISPRS workshop laser scanning 2011, 29–31 August 2011, Calgary, Canada, edited by: Lichti, D. D. and Habib, A. F., International Society for Photogrammetry and Remote Sensing (ISPRS), p. 6, 2011.
Rasika, A. K., Kerle, N., and Heuel, S. R. K. B.: Multi-scale texture and color segmentation of oblique airborne video data for damage classification, in: ISPRS 2006 : ISPRS mid-term symposium 2006 remote sensing: from pixels to processes, 8–11 May 2006, Enschede, the Netherlands, p. 8, 2006.
Rastiveis, H., Samadzadegan, F., and Reinartz, P.: A fuzzy decision making system for building damage map creation using high resolution satellite imagery, Nat. Hazards Earth Syst. Sci., 13, 455–472, https://doi.org/10.5194/nhess-13-455-2013, 2013.
Skybox imaging: Sub-meter satellite imagery and high-definition video: http://www.skyboximaging.com/, last access: 28 December 2013.
Stumpf, A. and Kerle, N.: Object-oriented mapping of landslides using random forests, Remote Sens. Environ., 115, 2564–2577, https://doi.org/10.1016/j.rse.2011.05.013, 2011.
Trimble: eCognition 8.7 reference book, Trimble Germany, München, Germany, 2011.
Voigt, S., Scheneiderhan, T., Twele, A., Gahler, M., Stein, E., and Mehl, H.: Rapid damage assessment and situation mapping: learning from the 2010 Haiti earthquake, Photogram. Eng. Remote Sens., 77, 923–931, 2011.
Weindorf, M., Vögtle, T., and Bähr, H. P.: An approach for the detection of damages in buildings from digital aerial information, in: Vrancea Earthquakes: Tectonics, Hazard and Risk Mitigation, edited by: Wenzel, F., Lungu, D., and Novak, O., Advances in Natural and Technological Hazards Research, Springer Netherlands, the Netherlands, 341–348, 1999.
Weinmann, M., Jutzi, B., and Mallet, C.: Feature relevance assessment for semantic interpretation of 3D point cloud data, ISPRS J. Photogram. Remote Sens. Spat. Inf. Sci., II-5/W2, 313–318, 2013.
Yamazaki, F. and Matsuoka, M.: Remote sensing technologies in post-disaster damage assessment, J. Earthq. Tsunami, 01, 193–210, https://doi.org/10.1142/S1793431107000122, 2007.
Zhang, Y. and Kerle, N.: Satellite remote sensing for near-real time data collection, in: Geospatial Information Technology for Emergency Response, Taylor & Francis, London, 75–102, 2008.
