Paper Info
Title
2D building change detection from high resolution satelliteimagery: A two-step hierarchical method based on 3D invariant primitives
Abstract
The analysis of remotely sensed data for object extraction is a key step in an increasing number of GIS (Geographic Information Science) applications, in particular for mapping, updating and change detection purposes. The main goal of this paper is to present an automatic method for detecting changes in a 2D building database, starting from recent satellite images. The workflow of our method is divided into two steps. 3D primitives, extracted from multiple images or from a correlation Digital Surface Model (DSM), are firstly collected for each building and matched with primitives derived from the existing database in order to achieve a final decision about acceptance or rejection. A specific algorithm, based on the DSM and a computed Digital Terrain Model (DTM), is subsequently used to extract new buildings. The method is here introduced and tested in two test areas, very different regarding the land use and topography. The outcomes of the method are assessed and show the good performance of our system, especially in terms of completeness, robustness and transferability.
Year
DOI
Venue
2010
10.1016/j.patrec.2009.10.012
Pattern Recognition Letters
Keywords
Field
DocType
change detection,quality assessment,new building,geographic information science,final decision,existing database,building change detection,automatic method,detection purpose,invariant primitive,building database,building vector database,two-step hierarchical method,computed digital terrain model,good performance,high resolution satelliteimagery,high resolution satellite imagery,digital terrain models,digital surface models,correlation digital surface model,digital terrain model,high resolution
Geographic information system,Signal processing,Change detection,Pattern recognition,Computer science,Robustness (computer science),Feature extraction,Digital elevation model,Artificial intelligence,Invariant (mathematics),Workflow
Journal
Volume
Issue
ISSN
31
10
Pattern Recognition Letters
Citations 
PageRank 
References 
6
0.65
12
Authors
4
Name
Order
Citations
PageRank
Nicolas Champion181.79
Didier Boldo2213.51
Marc Pierrot-Deseilligny3886.71
Georges Stamon47610.28