Abstract
In adjusting for discrepancies between adjacent airborne laser scanning (ALS) data strips, previous studies generally used conjugate features such as points, lines, and surface objects; however, irrespective of the types of features employed, the adjustment process relies upon the existence of suitable conjugate features within the overlapping area and the ability of the employed method to detect and extract the features. These limitations make the process complex and sometimes limit the applicability of developed methodologies because of a lack of suitable features in overlapping areas. To address these problems, this paper presents a methodology that uses the topological characteristics of the terrain itself, which is represented by a contour tree (CT). This approach provides a robust methodology without the restrictions involved in methods that employ conjugate features. Our method also makes the overall process of adjustment generally applicable and automated.
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Han, D., Lee, J., Kim, Y., Yu, K. (2006). Adjustment for Discrepancies Between ALS Data Strips Using a Contour Tree Algorithm. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2006. Lecture Notes in Computer Science, vol 4179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11864349_93
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DOI: https://doi.org/10.1007/11864349_93
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44630-9
Online ISBN: 978-3-540-44632-3
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