NDLI: Solving the horizontal conflation problem with a constrained Delaunay triangulation

Content Provider	Springer Nature Link
Author	Ledoux, Hugo Ohori, Ken Arroyo
Copyright Year	2016
Abstract	Datasets produced by different countries or organisations are seldom properly aligned and contain several discrepancies (e.g., gaps and overlaps). This problem has been so far almost exclusively tackled by snapping vertices based on a user-defined threshold. However, as we argue in this paper, this leads to invalid geometries, is error-prone, and leaves several discrepancies along the boundaries. We propose a novel algorithm to align the boundaries of adjacent datasets. It is based on a constrained Delaunay triangulation to identify and eliminate the discrepancies, and the alignment is performed without moving vertices with a snapping operator. This allows us to guarantee that the datasets have been properly conflated and that the polygons are geometrically valid. We present our algorithm, our implementation (based on the stable and fast triangulator in CGAL), and we show how it can be used it practice with different experiments with real-world datasets. Our experiments demonstrate that our approach is highly efficient and that it yields better results than snapping-based methods.
Starting Page	21
Ending Page	42
Page Count	22
File Format	PDF
ISSN	14355930
Journal	Journal of Geographical Systems
Volume Number	19
Issue Number	1
e-ISSN	14355949
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-09-09
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Conflation Edge-matching Triangulation Boundary alignment Data quality Regional/Spatial Science Geographical Information Systems/Cartography Urban Economics Econometrics Landscape/Regional and Urban Planning Computer Application in Social and Behavioral Sciences
Content Type	Text
Resource Type	Article
Subject	Earth-Surface Processes Geography, Planning and Development Economics and Econometrics

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