Abstract
In recent years object-based image analysis of digital elevation models acquired by airborne laser scanning gained in importance. Various applications for land cover classification (e.g. building and tree detection) already show promising results. Additionally to elevation rasters the original airborne laser scanning point cloud contains highly detailed 3D information. This paper introduces an integrative approach combining object-based image analysis and object-based point cloud analysis. This integrative concept is applied to building detection in the raster domain followed by a 3D roof facet delineation and classification in the point cloud. The building detection algorithm consists of a segmentation task, which is based on a fill sinks algorithm applied to the inverted digital surface model, and a rule-based classification task. The 340 buildings of the test site could be derived with 85% user’s accuracy and 92% producer’s accuracy. For each building object the original laser points are further investigated by a 3D segmentation (region growing) searching for planar roof patches. The finally delineated roof facets and their descriptive attributes (e.g. slope, 3D area) represent a useful input for a multitude of applications, such as positioning of solar-thermal panels and photovoltaics or snow load capacity modeling.
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References
Arge L, Chase J, Toma L, Vitter J, Wickremesinghe R, Halpin P, Urban D (2003) Efficient flow computation on massive grid terrain datasets. GeoInformatica, vol 7 (4), pp 283-313
Asselen S, Seijmonsbergen AC (2006) Expert-driven semiautomated geomorphological mapping for a mountainous area using a laser DTM. Geomorphology, vol 78 (3-4), pp 309-320
Bartunov O, Sigaev T (2007) GiST for PostgreSQL, http://www.sai.msu.su/~megera/postgres/gist/, last accessed: 9.3.2007
Benz UC, 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, vol 58 (3-4), pp 239-258
Brennan R, Webster TL (2006) Object-oriented land cover classification of lidar-derived surfaces. Canadian Journal of Remote Sensing, vol 32 (2), pp 162-172
Brenner C (2005) Building reconstruction from images and laser scanning. International Journal of Applied Earth Observation and Geoinformation, vol 6 (3-4), pp 187-198
Cain DJM (2007) PyGreSQL – PostgreSQL module for Python, http://www.pygresql.org, last accessed: 9.3.2007
Filin S, Pfeifer N (2005) Neighborhood systems for airborne laser scanner data. Photogrammetric Engineering and Remote Sensing, vol 71 (6), pp 743-755
Filin S, Pfeifer N (2006) Segmentation of airborne laser scanning data using a slope adaptive neighborhood. ISPRS Journal of Photogrammetry and Remote Sensing, vol 60 (2), pp 71-80
GRASS Development Team (2007) Geographic Resources Analysis Support System (GRASS) Software, ITC-irst, Trento Italy, http://grass.itc.it, last accessed: 9.3.2007
Haralick RM, Shapiro LG (1992) Computer and Robot Vision. Addison-Wesley Longman Publishing Co., Boston Massachusetts
Höfle B, Geist T, Rutzinger M, Pfeifer N (2007) Glacier surface segmentation using airborne laser scanning point cloud and intensity data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Espoo, Finland, on CD
Höfle B, Pfeifer N (2007) Correction of laser scanning intensity data: data and model-driven approaches. ISPRS Journal of Photogrammetry and Remote Sensing, doi:10.1016/j.isprsjprs.2007.05.008, accepted for publication
Höfle B, Rutzinger M, Geist T, Stötter J (2006) Using airborne laser scanning data in urban data management - set up of a flexible information system with open source components. In: Fendel E, Rumor M (eds) Proceedings of UDMS 2006: 25th Urban Data Management Symposium, Aalborg, on CD
Hollaus M, Wagner W, Kraus K (2005) Airborne laser scanning and usefulness for hydrological models. Advances in Geosciences, vol 5, pp 57-63
Jones E, Oliphant T, Peterson P et al. (2001-): SciPy: Open Source Scientific Tools for Python, http://www.scipy.org, , last accessed: 9.3.2007
Maier B, Tiede D, Dorren L (2006) Assessing mountain forest structure using airborne laser scanning and landscape metrics. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXVI (4/C42), on CD
Pfeifer N, Rutzinger M, Rottensteiner F, Mücke W, Hollaus M (2007) Extraction of building footprints from airborne laser scanning: comparison and validation techniques. Proceedings of the Urban Remote Sensing Joint Event 2007: 4th IEEE/GRSS ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas 6th International Symposium of Remote Sensing over Urban Areas, Paris, on CD
PostgreSQL Global Development Group (2007) PostgreSQL 8.1 Documentation, http://www.postgresql.org/docs/manuals/, last accessed: 9.3.2007
Python Software Foundation (2007) Python programming language, http://www.python.org, last accessed: 9.3.2007
Refractions Research Inc. (2007): PostGIS: Geographic Objects for PostgreSQL, PostGIS Manual, http://postgis.refractions.net/docs/, last accessed: 9.3.2007
Reitberger J, Krzystek P, Stilla U (2006) Analysis of full waveform lidar data for tree species classification. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXVI (3), pp 228-233
Rutzinger M, Höfle B, Geist T, Stötter J (2006a) Object-based building detection based on airborne laser scanning data within GRASS GIS environment. In: Fendel E, Rumor M (eds) Proceedings of UDMS 2006: 25th Urban Data Management Symposium, Aalborg, on CD
Rutzinger M, Höfle B, Pfeifer N, Geist T, Stötter J (2006b) Object-based analysis of airborne laser scanning data for natural hazard purposes using open source components. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXVI (4/C42), on CD
Sithole G (2005) Segmentation and classification of airborne laser scanner data. Publications on Geodesy of the Netherlands Commission of Geodesy, Delft
Tóv´ri D, Pfeifer N (2005) Segmentation based robust interpolation – a new approach to laser data filtering. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXVI (3/W19), pp 79-84
Tóv´ri D, Vögtle T (2004) Classification methods for 3D objects in laserscanning data. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXV (B3), on CD
Vögtle T, Steinle E, Tóv´ri D (2005) Airborne laserscanning data for determination of suitable areas for photovoltaics. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol XXXVI (3/W19), pp 215-220
Vosselman G, Kessels P, Gorte B (2005) The utilisation of airborne laser scanning for mapping. International Journal of Applied Earth Observation and Geoinformation, vol 6 (3/4), pp 177-186
Warmerdam F (2007) GDAL - Geospatial Data Abstraction Library. http://www.gdal.org, last accessed: 9.3.2007
Wehr A, Lohr U (1999) Airborne laser scanning - an introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing, vol 54 (2-3), pp 68-82
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Rutzinger, M., Höfle, B., Pfeifer, N. (2008). Object detection in airborne laser scanning data - an integrative approach on object-based image and point cloud analysis. In: Blaschke, T., Lang, S., Hay, G.J. (eds) Object-Based Image Analysis. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77058-9_35
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DOI: https://doi.org/10.1007/978-3-540-77058-9_35
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