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Remote Sens. 2014, 6(11), 10733-10749; doi:10.3390/rs61110733

Object-Based Analysis of Airborne LiDAR Data for Building Change Detection

1
School of Remote Sensing and Information Engineering, 129 Luoyu Road, Wuhan University, Wuhan 430079, China
2
Guangzhou Jiantong Surveying and Mapping Technology Development Ltd., 1027 Gaopu Road, Tianhe District, Guangzhou 510663, China
*
Author to whom correspondence should be addressed.
Received: 22 July 2014 / Revised: 21 September 2014 / Accepted: 22 October 2014 / Published: 6 November 2014
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Abstract

Building change detection is useful for land management, disaster assessment, illegal building identification, urban growth monitoring, and geographic information database updating. This study proposes an automatic method that applies object-based analysis to multi-temporal point cloud data to detect building changes. The aim of this building change detection method is to identify areas that have changed and to obtain from-to information. In this method, the data are first preprocessed to generate two sets of digital surface models (DSMs), digital elevation models, and normalized DSMs from registered old and new point cloud data. Thereafter, on the basis of differential DSM, candidates for changed building objects are identified from the points in the smooth areas by using a connected component analysis technique. The random sample consensus fitting algorithm is then used to distinguish the true changed buildings from trees. The changed building objects are classified as “newly built”, “taller”, “demolished” or “lower” by using rule-based analysis. Finally, a test data set consisting of many buildings of different types in an 8.5 km2 area is selected for the experiment. In the test data set, the method correctly detects 97.8% of buildings larger than 50 m2. The accuracy of the method is 91.2%. Furthermore, to decrease the workload of subsequent manual checking of the result, the confidence index for each changed object is computed on the basis of object features. View Full-Text
Keywords: change detection; object-based analysis; point cloud data; building change detection; object-based analysis; point cloud data; building
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Pang, S.; Hu, X.; Wang, Z.; Lu, Y. Object-Based Analysis of Airborne LiDAR Data for Building Change Detection. Remote Sens. 2014, 6, 10733-10749.

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