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Title
Technical Commission VII



Figure 3. Image and change detection results in a test area
(Blue: Newly-built, Pink: Demolished, Orange: Reconstructed)
3. RESULTS
The performance of change detection is assessed by comparing
the results obtained by the proposed approach to the reference
data acquired from image interpretation at a test area of Tokyo,
Japan. A building map of 2004 is used in this study. The aerial
images are acquired in 2008 by a multi-line digital airborne
sensor ADS40. The orthoimages & DSMs data are generated by
the Pixel Factory™ system of Astrium GEO-Information
Services. The resolution of DSMs is 0.5m and that of
orthoimages is 0.2m. Figure 3 shows the orthoimage of the test
area and change detection results of the proposed approach.
Table 1 shows the details of the change detection results for
newly-built buildings, demolished and reconstructed buildings.
39 buildings are detected from 44 changed buildings, and a total
detection rate is 88.6%. As for the details, 9 out of 13 newly-
built buildings are detected except for some very small ones.
All 16 demolished buildings, and 14 out of 15 reconstructed
buildings are detected. Among 4 undetected newly-built
buildings, 3 of them failed due to the influence of vegetation.
This shows the necessity to further improve the ability to
remove vegetation influence. On the other hand, detection of

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia

demolished and reconstructed buildings based on building
height estimation shows a high detection rate which proves the
effectiveness of this method. The proposed hybrid change
detection approach shows little misdetection and false-detection,
and is able to distinguish reconstructed buildings which are
difficult to be detected generally, and is possible to be applied
for building detection in the dense urban areas. Moreover, after
integrating this technique into a system for practical use, it is
found that the proposed approach can be used even to detect the
misregistration of building polygons in building maps in which
the positional accuracy of building polygons is worse and hence
can be used for accuracy check of building maps.

Detailed results

Newly-built | Demolished | Reconstructed







Changed Buildings 13 16 15
Detected Buildings 9 16 14
Total Accuracy (96) 88.6

Table 1. Detailed results of building change detection
4. CONCLUSIONS
This study presents a novel approach for building map updating
in dense urban areas. A scheme is proposed that allows efficient
integration of building object extraction and building height
estimation for detection of newly-built buildings, demolished
and reconstructed buildings, respectively. From the
experimental results of performance assessment, the proposed
approach presents wonderful results that it can detect almost all
demolished and reconstructed buildings, and most newly-built
buildings, and is effective to reduce the problems of
misdetection and false-detection. Besides, the proposed
approach can also be used to detect the misregistration of
building polygons in building maps and can be used for
accuracy check of building maps. This technique is already
integrated into a practical system for building maps updating.
Further improvement of this approach should be addressed on
building object extraction, especially for very small buildings
which are easily affected by surrounding vegetation.
References
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