DETECTION AND RECOGNITION OF CHANGES IN BUILDING GEOMETRY 
DERIVED FROM MULTITEMPORAL LASERSCANNING DATA 
T. Vógtle, E. Steinle 
IPF, University of Karlsruhe, EnglerstraBe 7, 76128 Karlsruhe, Germany — { voegtle,steinle } @ipf.uni-karlsruhe.de 
KEY WORDS: Change detection, Urban, Laser scanning, DEM/DTM, Segmentation, Comparison, Classification, Recognition 
ABSTRACT: 
The work presented is part of a project that aims at change detection in urban areas after strong earthquakes. Detection and 
classification of these changes are used to recognise building damages as an important information input for a disaster management 
system based on GIS techniques. Airborne laser scanning data was chosen for this approach, because of specific advantages like data 
acquisition of large areas in relatively short time or extensive independence on weather and lighting conditions. Modifications are 
detected by comparison of digital surface models (DSMs) acquired at two different dates (t; and t;). An analysis of solely a 
differential DSM (DSM(t,) - DSM(t,)) would lead to ambiguities, e.g. attachments or modifications of buildings could not be related 
to the affected buildings. Therefore, firstly a segmentation procedure based on a region growing algorithm is used to generate 
separate 3D objects. For each segment object-oriented features like border gradients or shape are extracted to classify into ‘building’, 
‘vegetation’ or ‘terrain’. After elimination of all non-building objects. the correspondence between the objects of the two laser 
scanning data sets has to be determined. At this step, new and teared-off buildings are extracted. The remaining 3D objects have to 
be controlled in terms of significant elevation changes and thus classified into ‘not-altered’, ‘added-on’ or ‘reduced’. First results in 
test area 'Karlsruhe' (approx. 8km x 2km) will be presented. 
KURZFASSUNG: 
In diesem Artikel werden Teile der Arbeit eines Projekts dargestellt, das sich mit der Ánderungserkennung in stadtischen Bereichen 
nach schweren Erdbeben beschäftigt. Das Ziel des Projekts ist die Entdeckung und Interpretation von Änderungen an Bauwerken um 
Gebäudeschäden zu finden, da sie wichtige Informationen für ein GIS-basiertes Katastrophenmanagementsystem darstellen. Im 
Projekt werden Daten des flugzeuggetragenen Laser Scannings benutzt, da diese Sensoren bestimmte Vorteile aufweisen, z.B. 
schnelle Informationsgewinnung über große Bereiche oder weitestgehende Witterungsunabhängikeit. Die eigentliche 
Anderungserkennung basiert auf dem Vergleich zweier digitaler Oberflichenmodelle (DOM), die zu verschiedenen Zeitpunkten 
erfasst wurden. Würde man ein reines Differenzen-DOM untersuchen, dann käme es zu Mehrdeutigkeiten, es kônnten z.B. Anbauten 
oder Veränderungen an einem Gebäude nicht immer zu diesem zugeordnet werden. Aus diesem Grund werden zuerst 3D-Objekte mit 
Hilfe eines region-growing basierten Segmentationsverfahren extrahiert. Für jedes Segment werden Merkmale wie 
Randgradientencharakteristiken oder Formparameter bestimmt, aufgrund denen das Objekt den Klassen 'Gebüude', 'Vegetation' 
oder "Gelüánde' zugeordnet wird. Danach werden die zu beiden Zeitpunkten aufgefundenen Gebäude auf ihre Überlagerung hin 
untersucht. Bei diesem Schritt werden Neubauten oder abgerissene Gebäude entdeckt. Die verbliebenen Objekte werden nun 
hinsichtlich signifikanter Höhenänderungen analysiert und dabei den Klassen 'unverándert' , ’aufgestockt” oder ’niedriger geworden’ 
zugewiesen. Erste Ergebnisse für das Testgebiet ’Karlsruhe’ (ungefähr 8km x 2km) werden gezeigt. 
time restrictions and for large areas has to be found. Airborne 
laser scanning - which has maturated to an operational system 
1. INTRODUCTION 
  
In this paper a method for change detection in urban areas is 
presented. It is focussed on changes of buildings which may be 
caused by planned, man-made modifications like rebuilding, 
extension, tear-off etc. or by natural disasters like strong 
earthquakes. To detect the latter ones is the main objective of a 
special project of the Collaborative Research Center 461 'strong 
earthquakes' (CRC 461, 2004). 
Building damages are one of the most important input 
information for a disaster management tool to optimise rescue 
activities. Therefore. a system for data acquisition under hard 
in the last years - was favoured for this special task. It provides 
3D coordinates for every measuring point by recording slant 
range to the reflecting surface point (laser sensor) and spatial 
orientation of the sensor (GPS / INS). The advantages of this 
system are high point density, high elevation accuracy, fast data 
acquisition of large areas, automatic determination of the height 
values, high independence of illumination conditions and 
robustness due to most weather conditions. Therefore, the 
system can be used also during night time and poor weather 
conditions which is a very important aspect for disaster 
management. Fortunately, there is no influence of shadows on 
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