A spatio-contextual probabilistic model for extracting linear features in hilly terrains from high-resolution DEM data
Author:
Affiliation:
1. School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA
2. Center of Excellence for Geospatial Information Science (CEGIS), U.S. Geological Survey, Rolla, MO, USA
Funder
National Science Foundation
U.S. Geological Survey
Publisher
Informa UK Limited
Subject
Library and Information Sciences,Geography, Planning and Development,Information Systems
Link
https://www.tandfonline.com/doi/pdf/10.1080/13658816.2018.1554814
Reference56 articles.
1. Orthogonal Polynomials Supported by Region Growing Segmentation for the Extraction of Terrain from Lidar Data
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3. Influence of DEM resolution on drainage network extraction: A multifractal analysis
4. Pairing semantics and object-based image analysis for national terrain mapping - a first-case scenario of cirques
5. The effect of resolution on terrain feature extraction
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