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CMRT09

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Bibliographic data

fullscreen: CMRT09

Monograph

Persistent identifier:
856955019
Author:
Stilla, Uwe
Title:
CMRT09
Sub title:
object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]
Scope:
X, 234 Seiten
Year of publication:
2009
Place of publication:
Lemmer
Publisher of the original:
GITC
Identifier (digital):
856955019
Illustration:
Illustrationen, Diagramme, Karten
Language:
English
Usage licence:
Attribution 4.0 International (CC BY 4.0)
Publisher of the digital copy:
Technische Informationsbibliothek Hannover
Place of publication of the digital copy:
Hannover
Year of publication of the original:
2016
Document type:
Monograph
Collection:
Earth sciences

Chapter

Title:
RAY TRACING AND SAR-TOMOGRAPHY FOR 3D ANALYSIS OF MICROWAVE SCATTERING AT MAN-MADE OBJECTS S. Auer, X. Zhu, S. Hinz, R. Bamler
Document type:
Monograph
Structure type:
Chapter

Contents

Table of contents

  • CMRT09
  • Cover
  • ColorChart
  • Title page
  • Workshop Committees
  • Program Committee:
  • Preface
  • Contents
  • EFFICIENT ROAD MAPPING VIA INTERACTIVE IMAGE SEGMENTATION O. Barinova, R. Shapovalov, S. Sudakov, A. Velizhev, A. Konushin
  • SURFACE MODELLING FOR ROAD NETWORKS USING MULTI-SOURCE GEODATA Chao-Yuan Lo, Liang-Chien Chen, Chieh-Tsung Chen, and Jia-Xun Chen
  • AUTOMATIC EXTRACTION OF URBAN OBJECTS FROM MULTI-SOURCE AERIAL DATA Adriano Mancini, Emanuele Frontoni and Primo Zingaretti
  • ROAD ROUNDABOUT EXTRACTION FROM VERY HIGH RESOLUTION AERIAL IMAGERY M. Ravenbakhsh, C. S. Fraser
  • ASSESSING THE IMPACT OF DIGITAL SURFACE MODELS ON ROAD EXTRACTION IN SUBURBAN AREAS BY REGION-BASED ROAD SUBGRAPH EXTRACTION Anne Grote, Franz Rottensteiner
  • VEHICLE ACTIVITY INDICATION FROM AIRBORNE LIDAR DATA OF URBAN AREAS BY BINARY SHAPE CLASSIFICATION OF POINT SETS W. Yaoa, S. Hinz, U. Stilla
  • TRAJECTORY-BASED SCENE DESCRIPTION AND CLASSIFICATION BY ANALYTICAL FUNCTIONS D. Pfeiffer, R. Reulke
  • 3D BUILDING RECONSTRUCTION FROM LIDAR BASED ON A CELL DECOMPOSITION APPROACH Martin Kada, Laurence McKinle
  • A SEMI-AUTOMATIC APPROACH TO OBJECT EXTRACTION FROM A COMBINATION OF IMAGE AND LASER DATA S. A. Mumtaz, K. Mooney
  • COMPLEX SCENE ANALYSIS IN URBAN AREAS BASED ON AN ENSEMBLE CLUSTERING METHOD APPLIED ON LIDAR DATA P. Ramzi, F. Samadzadegan
  • EXTRACTING BUILDING FOOTPRINTS FROM 3D POINT CLOUDS USING TERRESTRIAL LASER SCANNING AT STREET LEVEL Karim Hammoudi, Fadi Dornaika and Nicolas Paparoditis
  • DETECTION OF BUILDINGS AT AIRPORT SITES USING IMAGES & LIDAR DATA AND A COMBINATION OF VARIOUS METHODS Demir, N., Poli, D., Baltsavias, E.
  • DENSE MATCHING IN HIGH RESOLUTION OBLIQUE AIRBORNE IMAGES M. Gerke
  • COMPARISON OF METHODS FOR AUTOMATED BUILDING EXTRACTION FROM HIGH RESOLUTION IMAGE DATA G. Vozikis
  • SEMI-AUTOMATIC CITY MODEL EXTRACTION FROM TRI-STEREOSCOPIC VHR SATELLITE IMAGERY F. Tack, R. Goossens, G. Buyuksalih
  • AUTOMATED SELECTION OF TERRESTRIAL IMAGES FROM SEQUENCES FOR THE TEXTURE MAPPING OF 3D CITY MODELS Sébastien Bénitez and Caroline Baillard
  • CLASSIFICATION SYSTEM OF GIS-OBJECTS USING MULTI-SENSORIAL IMAGERY FOR NEAR-REALTIME DISASTER MANAGEMENT Daniel Frey and Matthias Butenuth
  • AN APPROACH FOR NAVIGATION IN 3D MODELS ON MOBILE DEVICES Wen Jiang, Wu Yuguo, Wang Fan
  • GRAPH-BASED URBAN OBJECT MODEL PROCESSING Kerstin Falkowski and Jürgen Ebert
  • A PROOF OF CONCEPT OF ITERATIVE DSM IMPROVEMENT THROUGH SAR SCENE SIMULATION D. Derauw
  • COMPETING 3D PRIORS FOR OBJECT EXTRACTION IN REMOTE SENSING DATA Konstantinos Karantzalos and Nikos Paragios
  • OBJECT EXTRACTION FROM LIDAR DATA USING AN ARTIFICIAL SWARM BEE COLONY CLUSTERING ALGORITHM S. Saeedi, F. Samadzadegan, N. El-Sheimy
  • BUILDING FOOTPRINT DATABASE IMPROVEMENT FOR 3D RECONSTRUCTION: A DIRECTION AWARE SPLIT AND MERGE APPROACH Bruno Vallet and Marc Pierrot-Deseilligny and Didier Boldo
  • A TEST OF AUTOMATIC BUILDING CHANGE DETECTION APPROACHES Nicolas Champion, Franz Rottensteiner, Leena Matikainen, Xinlian Liang, Juha Hyyppä and Brian P. Olsen
  • CURVELET APPROACH FOR SAR IMAGE DENOISING, STRUCTURE ENHANCEMENT, AND CHANGE DETECTION Andreas Schmitt, Birgit Wessel, Achim Roth
  • RAY TRACING AND SAR-TOMOGRAPHY FOR 3D ANALYSIS OF MICROWAVE SCATTERING AT MAN-MADE OBJECTS S. Auer, X. Zhu, S. Hinz, R. Bamler
  • THEORETICAL ANALYSIS OF BUILDING HEIGHT ESTIMATION USING SPACEBORNE SAR-INTERFEROMETRY FOR RAPID MAPPING APPLICATIONS Stefan Hinz, Sarah Abelen
  • FUSION OF OPTICAL AND INSAR FEATURES FOR BUILDING RECOGNITION IN URBAN AREAS J. D. Wegner, A. Thiele, U. Soergel
  • FAST VEHICLE DETECTION AND TRACKING IN AERIAL IMAGE BURSTS Karsten Kozempel and Ralf Reulke
  • REFINING CORRECTNESS OF VEHICLE DETECTION AND TRACKING IN AERIAL IMAGE SEQUENCES BY MEANS OF VELOCITY AND TRAJECTORY EVALUATION D. Lenhart, S. Hinz
  • UTILIZATION OF 3D CITY MODELS AND AIRBORNE LASER SCANNING FOR TERRAIN-BASED NAVIGATION OF HELICOPTERS AND UAVs M. Hebel, M. Arens, U. Stilla
  • STUDY OF SIFT DESCRIPTORS FOR IMAGE MATCHING BASED LOCALIZATION IN URBAN STREET VIEW CONTEXT David Picard, Matthieu Cord and Eduardo Valle
  • TEXT EXTRACTION FROM STREET LEVEL IMAGES J. Fabrizio, M. Cord, B. Marcotegui
  • CIRCULAR ROAD SIGN EXTRACTION FROM STREET LEVEL IMAGES USING COLOUR, SHAPE AND TEXTURE DATABASE MAPS A. Arlicot, B. Soheilian and N. Paparoditis
  • IMPROVING IMAGE SEGMENTATION USING MULTIPLE VIEW ANALYSIS Martin Drauschke, Ribana Roscher, Thomas Läbe, Wolfgang Förstner
  • REFINING BUILDING FACADE MODELS WITH IMAGES Shi Pu and George Vosselman
  • AN UNSUPERVISED HIERARCHICAL SEGMENTATION OF A FAÇADE BUILDING IMAGE IN ELEMENTARY 2D - MODELS Jean-Pascal Burochin, Olivier Tournaire and Nicolas Paparoditis
  • GRAMMAR SUPPORTED FACADE RECONSTRUCTION FROM MOBILE LIDAR MAPPING Susanne Becker, Norbert Haala
  • Author Index
  • Cover

Full text

In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 
along the elevation direction. It is located at the layover area. 
Fig.9 gives a closer look to the ground truth at that area. The 
left image shows the convention center visualized in Google 
Earth in which the pixel of interest is included in the area 
marked by a red block. The right image tells that the returns 
from the roof of the convention center and from the plaza near 
ground mainly contribute to the measurement of this pixel. 
Figure 8: TerraSAR-X intensity image of convention center, 
Las Vegas; selected pixel marked by green spot 
Figure 9: corresponding aerial image, © Google Earth 
Figure 10: Model of the ground truth for the pixel of interest 
For simulation, we simplify the ground truth to the following 
model as depicted in Fig. 10. The incidence angle for the 
acquisition is adapted to the real SAR acquisition and, hence, is 
31.8 degrees. The taller building refers to the convention center 
which has a height of about 24m, while the lower building 
stands for the plaza near ground. Heights are measured over 
ground. The measurement for the pixel of interest refers to the 
integral of the returns from the objects included in the strip 
highlighted in blue color. For simulation purposes, two box 
models are used for modeling both the plaza and the convention 
center (Figure 11). The roughness of the plaza’s surface is 
assumed to be slightly higher than the roughness of walls and 
roof parts of the convention center. 
3.2 Simulation vs. real data 
The reflectivity profile of the resolution cell along elevation 
direction is derived using the simulation concept described in 
Section 2. Pixel selection is adapted to extracted real data as 
shown in Figure 8. Afterwards, the resulting slice in elevation is 
displayed in height over ground geometry (Figure 12). Heights 
of reflecting objects are reliably extracted as two single bounce 
contributions at heights of 3 and 24 meters. 
Figure 11: 3D model scene containing two boxes for 
approximating layover effect (flat box: 20 m x 30 m x 
3 m; tall box: 15 m x 15 m x 24 m); diffuse 
backscattering behaviour at all box surfaces 
Figure 12: discrete elevation coordinates for backscattering 
objects; step-width in elevation: 1 meter 
Fig. 13 shows the result of tomographic analysis for the 
corresponding position in real TerraSAR-X data. The reflection 
profile has been calculated with the approach described in (Zhu 
et al., 2008). As input data, 16 TerraSAR-X spotlight images 
with an across-track baseline range of 270m have been used. 
The peaks in reflection profile show nice correspondence with 
the simulated results, which underlines the accurate geometric 
properties of the simulation. However, it has to be noted that 
accurate estimation of intensity proportions is not possible as 
ground truth for surface properties was not available. At this 
point, simulated intensity values only indicate a stronger diffuse 
backscattering from the plaza which is also visible in the 
reflectivity map extracted from real SAR data. Enhanced 
information about the scattering behaviour of the plaza and the 
convention center may enable better simulation results in the
	        

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