Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/14861
Title: Identifying curvature of overpass mountain roads in Iran from high spatial resolution remote sensing data
Contributor(s): Alian, Sahar (author); Tolpekin, Valentyn A (author); Bijker, Wietske (author); Kumar, Lalit  (author)orcid 
Publication Date: 2014
DOI: 10.1016/j.jag.2013.05.002
Handle Link: https://hdl.handle.net/1959.11/14861
Abstract: Digital curve identification from remote sensing data is difficult in continuous objects such as roads. Use of high spatial resolution images can increase geometrical details and accuracy of estimation and detect curvy segments from the road boundary. We detect a road as a curve in 2D raster grid and analyze its shape using fuzzy c-means and alpha shapes. Two approaches identify curvature from the polylines on two sides of the road. Image resolution, radius of alpha circles and size of moving window are the three main parameters for detection of curvy segments. Lower resolution, larger alpha circles and larger moving windows decrease the chance of detecting sharp and narrow curve segments.
Publication Type: Journal Article
Source of Publication: International Journal of Applied Earth Observation and Geoinformation, v.26, p. 21-25
Publisher: Elsevier BV
Place of Publication: Netherlands
ISSN: 1872-826X
1569-8432
Fields of Research (FoR) 2008: 090903 Geospatial Information Systems
090905 Photogrammetry and Remote Sensing
Fields of Research (FoR) 2020: 401302 Geospatial information systems and geospatial data modelling
401304 Photogrammetry and remote sensing
Socio-Economic Objective (SEO) 2008: 960604 Environmental Management Systems
Socio-Economic Objective (SEO) 2020: 189999 Other environmental management not elsewhere classified
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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