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Cited by 21Automated Road and Building ExtractionRemote-Sensing Image ClassificationPoint processes and geometric inequalities

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Forest point processes for the automatic extraction of networks in raster data

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Schmidt, Alena, Lafarge, Florent, Brenner, Claus, Rottensteiner, Franz, Heipke, Christian·2017·ISPRS Journal of Photogrammetry and Remote Sensing
DOI 10.1016/j.isprsjprs.2017.01.012
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Metadata

Authors
Schmidt, A., Lafarge, F., Brenner, C., Rottensteiner, F., & Heipke, C.
Affiliations
  • Leibniz University Hannover (DE)
  • Institut national de recherche en sciences et technologies du numérique (FR)
Corresponding author
Schmidt, Alena
ORCID
Venue
ISPRS Journal of Photogrammetry and Remote Sensing
Publisher
Elsevier BV
Published
2017-04
Volume
126
Pages
38-55
ISSN
0924-2716 (ISSN-L)
DOI
10.1016/j.isprsjprs.2017.01.012
OpenAlex
W2587265055
Cited by
21
References
1
Citations by year
2025: 1 · 2024: 1 · 2022: 2 · 2021: 2 · 2020: 3 · 2019: 5 · 2018: 6 · 2017: 1
FWCI
3.45
Type
journal article
Language
en
Open access
Licence
Locations
  • ISPRS Journal of Photogrammetry and Remote Sensing (publishedVersion)
  • HAL (submittedVersion, other-oa)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Automated Road and Building Extraction
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Remote-Sensing Image Classification
  • Physical Sciences › Mathematics › Applied Mathematics › Point processes and geometric inequalities
Keywords
network extraction, raster data, spatial point processes, reversible jump MCMC, energy minimization, river extraction, tidal channels, digital terrain model, graph model, stochastic sampling

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CoChat. (2026). Citation check: Forest point processes for the automatic extraction of networks in raster data. https://app.cochat.ai/papers/10.1016/j.isprsjprs.2017.01.012
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Schmidt, A., Lafarge, F., Brenner, C., Rottensteiner, F., & Heipke, C. (2017). Forest point processes for the automatic extraction of networks in raster data. ISPRS Journal of Photogrammetry and Remote Sensing. https://doi.org/10.1016/j.isprsjprs.2017.01.012