[Aguilar, M. a, Saldana, M.M., Aguilar, F.J., 2013. GeoEye-1 and WorldView-2 pan-sharpened imagery for object-based classification in urban environments. International Journal of Remote Sensing, 34, 7, 2583–2606.10.1080/01431161.2012.747018]Search in Google Scholar
[Baatz, M., Schäpe, A., Strobl, J., Blaschke, T., Griesebner, G., 2000. Multiresolution Segmentation - an optimization approach for high quality multi-scale image segmentation. Angewandte Geographische Informationsverarbeitung, 12, 12–23. Retrieved from internal-pdf://xn--baatz_schpe_2000-3891068462-jkc/Baatz_Sch?pe_2000.PDF]Search in Google Scholar
[Banko, G., Mansberger, R., Gallaun, H., Grillmayer, R., Prüller, R., Riedl, M., Stemberger, W., Steinnocher, K., Walli, A., 2014. Land Information System Austria (LISA). In: Manakos, I., Braun, M. (Eds.): Land Use and Land Cover Mapping in Europe. Springer, 18, pp. 237–254.10.1007/978-94-007-7969-3_15]Search in Google Scholar
[Barredo, J.I., 2009. Normalised flood losses in Europe: 1970–2006. Natural Hazards and Earth System Science, 9, 1, 97–104.10.5194/nhess-9-97-2009]Search in Google Scholar
[Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, I., Heynen, M., 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, 58, 3–4, 239–258.10.1016/j.isprsjprs.2003.10.002]Search in Google Scholar
[BEV, 2015. Fernerkundung-Folder. [Brochure of the remote sensing products of the BEV]. Retrieved from http://www.bev.gv.at/pls/portal/docs/page/bev_portal_content_allgemein/0200_produkte/pdf-doku/fernerkundung-folder.pdf (In German.)]Search in Google Scholar
[Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65, 1, 2–16.10.1016/j.isprsjprs.2009.06.004]Search in Google Scholar
[Blaschke, T., Lang, S., Hay, G.J., 2008. Object-Based Image Analysis. Spatial Concepts for Knowledge-Driven Remote Sensing Applications, 418. http://doi.org/10.1007/978-3-540-88183-4]Search in Google Scholar
[Blöschl, G., Gaál, L., Hall, J., Kiss, A., Komma, J., Nester, T., Parajka, J., Perdigão, R. A. P., Plavcová, L., Rogger, M., Salinas, J. L., Vigkione, A., 2015. Increasing river floods: fiction or reality? WIREs Water. http://doi.org/10.1002/wat2.1079]Search in Google Scholar
[BMLFUW, 2006. Hochwasserzonierung Austria - HORA. Wien. Retrieved from http://www.bmlfuw.gv.at/wasser/schutz_vor_naturgefahren/beratung_information/hora02.html (In German.)]Search in Google Scholar
[Breiman, L., 2001. Random forests. Machine Learning, 45, 5–32.10.1023/A:1010933404324]Search in Google Scholar
[Cammerer, H., Thieken, A.H., 2013. Historical development and future outlook of the flood damage potential of residential areas in the Alpine Lech Valley (Austria) between 1971 and 2030. Regional Environmental Change, 13, 5, 999–1012.10.1007/s10113-013-0407-9]Search in Google Scholar
[Carlson, T.N., Ripley, D.A., 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62, 3, 241–252.10.1016/S0034-4257(97)00104-1]Search in Google Scholar
[Cheng, Y., 1995. Mean Shift, Mode Seeking, and Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 17, 8,. http://doi.org/0162-8828/95$04.00]Search in Google Scholar
[Comaniciu, D., Meer, P., 2002. Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, 5, 603–619.10.1109/34.1000236]Search in Google Scholar
[Cretu, A.-M., Payeur, P., 2013. Building Detection in Aerial Images Based on Watershed and Visual Attention Feature Descriptors. In: 2013 International Conference on Computer and Robot Vision, IEEE, Regina, CA, pp. 265–272.10.1109/CRV.2013.8]Search in Google Scholar
[Dare, P.M., 2005. Shadow analysis in high-resolution satellite imagery of urban areas. Photogrammetric Engineering & Remote Sensing, 71, 2, 169–177.10.14358/PERS.71.2.169]Search in Google Scholar
[de Moel, H., van Alphen, J., Aerts, J.C.J.H., 2009. Flood maps in Europe – methods, availability and use. Natural Hazards and Earth System Science, 9, 2, 289–301.10.5194/nhess-9-289-2009]Search in Google Scholar
[de Risi, R., Jalayer, F., de Paola, F., Iervolino, I., Giugni, M., Topa, M.E., Mbuya, E., Kyessi, A., Manfredi, G., Gasparini, P., 2013a. Flood risk assessment for informal settlements. Natural Hazards, 69, 1, 1003–1032.10.1007/s11069-013-0749-0]Search in Google Scholar
[de Risi, R., Jalayer, F., Manfredi, G., Carozza, S., 2013b. VISK: a GIS-compatible platform for micro-scale assessment of flooding risk un urban areas. In: 4th ECCOMAS Thematic Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, COMPDYN, Kos Island, Greece.]Search in Google Scholar
[Di Baldassarre, G., Viglione, A., Carr, G., Kuil, L., Salinas, J. L., Blöschl, G., 2013. Socio-hydrology: Conceptualising human-flood interactions. Hydrology and Earth System Sciences, 17, 8, 3295–3303.10.5194/hess-17-3295-2013]Search in Google Scholar
[Dietterich, T.G., 2000. Ensemble methods in machine learning. Multiple Classifier Systems, 1857, 1–15.10.1007/3-540-45014-9_1]Search in Google Scholar
[DORIS, 2015. Digital Upper Austrian spatial information system. Data available under http://doris.ooe.gv.at]Search in Google Scholar
[Dorn, H., Vetter, M., Höfle, B., 2014. GIS-based roughness derivation for flood simulations: A comparison of orthophotos, LiDAR and Crowdsourced Geodata. Remote Sensing, 6, 2, 1739–1759.10.3390/rs6021739]Search in Google Scholar
[EG, 2007. Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks. European Commision, Brussels, pp. 27–34.]Search in Google Scholar
[FOEN, 1999. Risikoanalyse bei gravitativen Naturgefahren Umwelt-Materialien. [Risk analysis for natural hazards.]. Vol. 107. Schweizerische Eidgenossenschaft, Bern. (In German.)]Search in Google Scholar
[Fukunaga, K., Hostetler, L., 1975. The estimation of the gradient of a density function, with applications in pattern recognition. IEEE Transactions on Information Theory, 21, 1, 32–40.10.1109/TIT.1975.1055330]Search in Google Scholar
[Gocht, M., Schröter, K., Ostrowski, M., Rubin, C., 2009. EWASE — Early Warning Systems Efficiency – risk assessment and efficiency analysis. Water, 136–137.10.1201/9780203883020.ch87]Search in Google Scholar
[Hartmann, D.L., Klein Tank, A.M.G., Rusticucci, M., Alexander, L. V., Brönnimann, S., Charabi, Y., Dentener, F.J., Dlugokencky, E.J., Easterling, D.R., Kaplan, A., Soden, B.J., Thorne, P.W., Wild, M., Zhai, P.M., 2013. Observations: Atmosphere and Surface, in The Physical Science Basis. In: Stocker, T.F., Qin, G.-K.P.D. (Eds.): Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.]Search in Google Scholar
[Hermosilla, T., Ruiz, L.A., Recio, J.A., Estornell, J., 2011. Evaluation of automatic building detection approaches combining high resolution images and LiDAR data. Remote Sensing, 3, 12, 1188–1210. http://doi.org/10.3390/rs3061188]Search in Google Scholar
[Huttenlau, M., Schneeberger, B., Winter, B., Reiss, J., Stötter, J., 2015. Analysis of the loss probability relation on a community level: a contribution to a comprehensive flood risk assessment. In: Sener, S.M., Brebbia, C.A., Ozcevik, O. (Eds.): Disaster Management and Human Health Risk IV WIT Press, Southhampton, UK, pp. 171–182.10.2495/DMAN150161]Search in Google Scholar
[Inglada, J., Christophe, E., 2009. The Orfeo Toolbox remote sensing image processing software. In: IEEE International Geoscience and Remote Sensing Symposium, IEEE, Cape Town, SA, pp. 733–736.10.1109/IGARSS.2009.5417481]Search in Google Scholar
[Kressler, F.P., Steinnocher, K., Franzen, M., 2005. Object-oriented classification of orthophotos to support update of spatial databases. In: International Geoscience and Remote Sensing Symposium, 1, C, IEEE, Seoul, KR, pp. 253–256.]Search in Google Scholar
[Leone, F., Lavigne, F., Paris, R., Denain, J.C., Vinet, F., 2011. A spatial analysis of the December 26th, 2004 tsunami-induced damages: Lessons learned for a better risk assessment integrating buildings vulnerability. Applied Geography, 31, 1, 363–375.10.1016/j.apgeog.2010.07.009]Search in Google Scholar
[Merz, B., Thieken, A.H., 2004. Flood risk analysis: Concepts and challenges. Österreichische Wasser- und Abfallwirtschaft, 56, 3–4, 27–34.]Search in Google Scholar
[Myint, S.W., Gober, P., Brazel, A., Grossman-Clarke, S., Weng, Q., 2011. Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sensing of Environment, 115, 5, 1145–1161. http://doi.org/10.1016/j.rse.2010.12.017]Search in Google Scholar
[Myneni, R.B., Hall, F.G., Sellers, P.J., Marshak, A.L., 1995. Interpretation of spectral vegetation indexes. IEEE Transactions on Geoscience and Remote Sensing, 33, 2, 481–486. http://doi.org/10.1109/36.377948]Search in Google Scholar
[Nachtnebel, H., Apperl, B., 2013. Wasserwirtschaftliche Entwicklung in Überflutungsgebieten: Instumentenevaluierungsstudie. [Development in flood prone areas: assessment of flood management alternatives]. IWHW BOKU, Vienna. (In German.)]Search in Google Scholar
[Nachtnebel, H., Apperl, B., 2014. Hochwasserrisikomanagementplan Gleisdorf. Pilotprojekt zur Umsetzung der EU-Hochwasserrichtlinie. [Flood risk management and emergency plan for the city of Gleisdorf (Styria)]. IWHW BOKU, Vienna. (In German.)]Search in Google Scholar
[Nachtnebel, H., Apperl, B., 2015. Beurteilung des Hochwasser-Schadenspotenzials unter dynamischen Bedingungen. Österreichische Wasser- Und Abfallwirtschaft, 67, 3–4, 120–130.10.1007/s00506-015-0220-4]Search in Google Scholar
[Neuhold, C., Nachtnebel, H., 2012. Beurteilung des Hochwasserrisikos: Skalenaspekte und Umsetzung. [Assessing flood risk: Aspects of scale and implementation]. Österreichische Wasser- und Abfallwirtschaft, 64, 5–6, 323–328. (In German.)10.1007/s00506-012-0407-x]Search in Google Scholar
[RIWA-T, 2006. Technische Richtlinie für die Bundeswasserbauverwaltung. [Technical Guidelines for the Federal Water Construction]. Austrian Ministry for Agriculture, Forestry, Environment and Water Management, Vienna. (In German.)]Search in Google Scholar
[Rottensteiner, F., Trinder, J., Clode, S., Kubik, K., 2007. Building detection by fusion of airborne laser scanner data and multi-spectral images: Performance evaluation and sensitivity analysis. ISPRS Journal of Photogrammetry and Remote Sensing, 62, 2, 135–149.10.1016/j.isprsjprs.2007.03.001]Search in Google Scholar
[Sanyal, J., Lu, X.X., 2004. Application of remote sensing in flood management with special reference to monsoon Asia: A review. Natural Hazards, 33, 283–301.10.1023/B:NHAZ.0000037035.65105.95]Search in Google Scholar
[Sanyal, J., Lu, X.X., 2005. Remote sensing and GIS-based flood vulnerability assessment of human settlements: A case study of Gangetic West Bengal, India. Hydrological Processes, 19, 18, 3699–3716.10.1002/hyp.5852]Search in Google Scholar
[Schulz, K., Schwingshandl, A., 2014. Wasserwirtschaftliche Entwicklung in Überflutungsgebieten - Raumnutzung und Maßnahmenwirkung. [Development in floodplain areas - land use and effectiveness of measures]. IWHW BOKU & riocom, Vienna. (In German.)]Search in Google Scholar
[Schumann, G., Matgen, P., Hoffmann, L., Hostache, R., Pappenberger, F., Pfister, L., 2007. Deriving distributed roughness values from satellite radar data for flood inundation modelling. Journal of Hydrology, 344, 1–2, 96–111.10.1016/j.jhydrol.2007.06.024]Search in Google Scholar
[Taubenböck, H., Wurm, M., Netzband, M., Zwenzner, H., Roth, A., Rahman, A., Dech, S., 2011. Flood risks in urbanized areas - Multi-sensoral approaches using remotely sensed data for risk assessment. Natural Hazards and Earth System Science, 11, 2, 431–444.10.5194/nhess-11-431-2011]Search in Google Scholar
[Thieken, A.H., Kreibich, H., Müller, M., Merz, B., 2007. Coping with floods: preparedness, response and recovery of flood-affected residents in Germany in 2002. Hydrological Sciences Journal, 52, 5, 1016–1037.10.1623/hysj.52.5.1016]Search in Google Scholar
[Tucker, C.J., Pinzon, J.E., Brown, M.E., Slayback, D.A., Pak, E.W., Mahoney, R., Vermote, E.F., El Saleous, N., 2005. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing, 26, 20, 4485–4498.10.1080/01431160500168686]Search in Google Scholar
[UNISDR, 2011. Global Assessment Report on Disaster Risk Reduction: Revealing Risk, Redefining Development. United Nations, Geneve, 178 p.]Search in Google Scholar
[van der Sande, C.J., de Jong, S.M., de Roo, A.P.J., 2003. A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment. International Journal of Applied Earth Observation and Geoinformation, 4, 3, 217–229.10.1016/S0303-2434(03)00003-5]Search in Google Scholar
[Vojtek, M., Vojteková, J., 2016. Flood hazard and flood risk assessment at the local spatial scale: a case study. Geomatics, Natural Hazards and Risk, (in press). http://doi.org/10.1080/19475705.2016.1166874]Search in Google Scholar
[Vu, T.T., Yamazaki, F., Matsuoka, M., 2009. Multi-scale solution for building extraction from LiDAR and image data. International Journal of Applied Earth Observation and Geoinformation, 11, 4, 281–289.10.1016/j.jag.2009.03.005]Search in Google Scholar
[Wegner, J.D., Hänsch, R., Thiele, A., Sörgel, U., 2011. Building detection from one orthophoto and high-resolution InSAR data using conditional random fields. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4, 1, 83–91.10.1109/JSTARS.2010.2053521]Search in Google Scholar
[Zazo, S., Molina, J.L., Rodriguez-Gonzalvez, P., 2015. Analysis of flood modeling through innovative geomatic methods. Journal of Hydrology, 524, 522–537.10.1016/j.jhydrol.2015.03.011]Search in Google Scholar