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

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

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

Open access
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
Open this paper in CoChat — free account

Overview

Integrity signals

Registry

Crossref · 10.1016/j.isprsjprs.2017.01.012

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 1 references

Research works printed but not linked: 60

  1. Bas, 2011, Principal curves as skeletons of tubular objects, Neuroinformatics, 9, 181, 10.1007/s12021-011-9105-2 · DOI
  2. Baumgartner, 1999, Automatic road extraction based on multi-scale, grouping, and context, Photogram. Eng. Remote Sensing, 65, 777
  3. Benedek, 2014, Moving target analysis in ISAR image sequences with a multiframe marked point process model, IEEE Trans. Geosci. Remote Sensing, 52, 2234, 10.1109/TGRS.2013.2258927 · DOI
  4. Bentabet, 2003, Road vectors update using SAR imagery: a snake-based method, IEEE Trans. Geosci. Remote Sensing, 41, 1785, 10.1109/TGRS.2003.813850 · DOI
  5. Butenuth, 2012, Network snakes: graph-based object delineation with active contour models, Machine Vis. Appl., 23, 91, 10.1007/s00138-010-0294-8 · DOI
  6. Chothani, 2011, Automated tracing of neurites from light microscopy stacks of images, Neuroinformatics, 9, 263, 10.1007/s12021-011-9121-2 · DOI
  7. Descombes, 2002, Marked point process in image analysis, IEEE Signal Process. Mag., 19, 77, 10.1109/MSP.2002.1028354 · DOI
  8. Fagherazzi, 1999, Tidal networks – automatic network extraction and preliminary scaling features from digital terrain maps, Water Resour. Res., 35, 3891, 10.1029/1999WR900236 · DOI
  9. Fairfield, 1991, Drainage network from grid digital elevation models, Water Resour. Res., 27, 709, 10.1029/90WR02658 · DOI
  10. Fischler, 1981, Detection of roads and linear structure in low resolution aerial imagery using a multi-source knowledge integration technique, Comput. Graph. Image Process., 15, 201, 10.1016/0146-664X(81)90056-3 · DOI
  11. Freeman, 1991, Calculating catchment area with divergent flow based on a regular grid, Comput. Geosci., 17, 413, 10.1016/0098-3004(91)90048-I · DOI
  12. Gamba, 2006, Improving urban road extraction in high-resolution images exploiting directional filtering, perceptual grouping, and simple topological concepts, IEEE Geosci. Remote Sensing Lett., 3, 387, 10.1109/LGRS.2006.873875 · DOI
  13. Geman, 1984, Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Trans. Pattern Anal. Machine Intell., 6, 721, 10.1109/TPAMI.1984.4767596 · DOI · Paper page
  14. Geman, 1996, An active testing model for tracking roads in satellite images, IEEE Trans. Pattern Anal. Machine Intell., 18, 1, 10.1109/34.476006 · DOI
  15. Gerke, 2004, Graph-supported verification of road databases, ISPRS J. Photogram. Remote Sensing, 58, 152, 10.1016/j.isprsjprs.2003.09.003 · DOI
  16. Green, 1995, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, 82, 711, 10.1093/biomet/82.4.711 · DOI
  17. Grote, 2012, Road network extraction in suburban areas, Photogram. Rec., 27, 8, 10.1111/j.1477-9730.2011.00670.x · DOI
  18. Gruber, 2009, Land-surface parameters and objects in hydrology, vol. 33, 171
  19. Gruen, 1995, Road extraction from aerial and satellite images by dynamic programming, ISPRS J. Photogram. Remote Sensing, 50, 11, 10.1016/0924-2716(95)98233-P · DOI
  20. Hastings, 1970, Monte Carlo sampling methods using Markov chains and their applications, Biometrika, 57, 97, 10.1093/biomet/57.1.97 · DOI · Paper page
  21. Hinz, 2003, Automatic extraction of urban road networks from multi-view aerial imagery, ISPRS J. Photogram. Remote Sensing, 58, 83, 10.1016/S0924-2716(03)00019-4 · DOI
  22. Holmgren, 1994, Multiple flow direction algorithms for runoff modelling in grid based elevation models: an empirical evaluation, Hydrol. Process., 8, 327, 10.1002/hyp.3360080405 · DOI
  23. Huang, 2013, A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data, ISPRS J. Photogram. Remote Sensing, 79, 29, 10.1016/j.isprsjprs.2013.02.004 · DOI
  24. Hu, 2007, Road network extraction and intersection detection from aerial images by tracking road footprints, IEEE Trans. Geosci. Remote Sensing, 45, 4144, 10.1109/TGRS.2007.906107 · DOI
  25. Jasiewicz, 2011, A new GRASS GIS toolkit for Hortonian analysis of drainage networks, Comput. Geosci., 37, 1162, 10.1016/j.cageo.2011.03.003 · DOI
  26. Kass, 1988, Snakes: active contour models, Int. J. Comput. Vis., 1, 321, 10.1007/BF00133570 · DOI
  27. Katartzis, 2001, A model-based approach to the automatic extraction of linear features from airborne images, IEEE Trans. Geosci. Remote Sensing, 39, 2073, 10.1109/36.951102 · DOI
  28. Kirbas, 2004, A review of vessel extraction techniques and algorithms, Comput. Surveys, 36, 81, 10.1145/1031120.1031121 · DOI
  29. Kirkpatrick, 1983, Optimization by simulated annealing, Sci. New Ser., 220, 671
  30. Kreher, B.W., 2007. Detektion von Hirnnervenfasern auf der Basis von diffusionsgewichteten Magnetresonanzdaten. Dissertation der Fakultät für Angewandte Wissenschaften der Albert-Ludwigs-Universität Freiburg im Breisgau.
  31. Kumar, 2003, Discriminative random fields: a discriminative framework for contextual interaction in classification, Proc. IEEE Int. Conf. Comput. Vis., 2, 1150, 10.1109/ICCV.2003.1238478 · DOI
  32. Lacoste, 2005, Point processes for unsupervised line network extraction in remote sensing, IEEE Trans. Pattern Anal. Machine Intell., 27, 1568, 10.1109/TPAMI.2005.206 · DOI
  33. Lafarge, 2010, Geometric feature extraction by a multimarked point process, IEEE Trans. Pattern Anal. Machine Intell., 32, 1597, 10.1109/TPAMI.2009.152 · DOI
  34. Lesage, 2009, A review of 3D vessel lumen segmentation techniques: models, features and extraction schemes, Med. Image Anal., 13, 819, 10.1016/j.media.2009.07.011 · DOI
  35. Lohani, 2001, Application of airborne scanning laser altimetry to the study of tidal channel geomorphology, ISPRS J. Photogram. Remote Sensing, 56, 100, 10.1016/S0924-2716(01)00041-7 · DOI
  36. Lohani, 2006, Extraction of tidal channel networks from aerial photographs alone and combined with laser altimetry, Int. J. Remote Sensing, 27, 5, 10.1080/01431160500206692 · DOI
  37. Mallet, 2010, A marked point process for modeling lidar waveforms, IEEE Trans. Image Process., 19, 3204, 10.1109/TIP.2010.2052825 · DOI
  38. Marín, 2011, A new supervised method for blood vessel segmentation in retinal images by using gray-level and moment invariants-based features, IEEE Trans. Med. Imaging, 30, 146, 10.1109/TMI.2010.2064333 · DOI
  39. Mason, 2006, Extraction of tidal channel networks from airborne scanning laser altimetry, ISPRS J. Photogram. Remote Sensing, 61, 67, 10.1016/j.isprsjprs.2006.08.003 · DOI
  40. Mayer, 2006, A test of automatic road extraction approaches, Int. Arch. Photogram. Remote Sensing Spatial Inform. Sci., 36, 209
  41. Mena, 2005, An automatic method for road extraction in rural and semi-urban areas starting from high resolution satellite imagery, Pattern Recogn. Lett., 26, 1201, 10.1016/j.patrec.2004.11.005 · DOI
  42. Metropolis, 1953, Equation of state calculations by fast computing machines, J. Chem. Phys., 21, 1087, 10.1063/1.1699114 · DOI · Paper page
  43. Montoya-Zegarra, J., Wegner, J., Ladicky, L., Schindler, K., 2014. Mind the gap: modeling local and global context in (road) networks. In: German Conference on Pattern Recognition (GCPR). · DOI
  44. Movaghati, 2010, Road extraction from satellite images using particle filtering and extended Kalman filtering, IEEE Trans. Geosci. Remote Sensing, 48, 2807, 10.1109/TGRS.2010.2041783 · DOI
  45. O’Callaghan, 1984, The extraction of drainage networks from digital elevation data, Comput. Vis. Graph. Image Process., 28, 323, 10.1016/S0734-189X(84)80011-0 · DOI
  46. Ortner, 2007, Building outline extraction from digital elevation models using marked point processes, Int. J. Comput. Vis., 72, 107, 10.1007/s11263-005-5033-7 · DOI
  47. Poullis, 2010, Delineation and geometric modeling of road networks, ISPRS J. Photogram. Remote Sensing, 65, 165, 10.1016/j.isprsjprs.2009.10.004 · DOI
  48. Quinn, 1991, The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models, Hydrol. Process., 5, 59, 10.1002/hyp.3360050106 · DOI
  49. Rochery, 2006, Higher order active contours, Int. J. Comput. Vis., 69, 27, 10.1007/s11263-006-6851-y · DOI
  50. Schmidt, 2015, A graph based model for the detection of tidal channels using marked point process, Int. Arch. Photogram. Remote Sensing Spatial Inform. Sci., XL-3/W3, 115, 10.5194/isprsarchives-XL-3-W3-115-2015 · DOI
  51. Schmidt, 2016, Network detection in raster data using marked point processes, ISPRS Arch. Photogram. Remote Sensing Spatial Inform. Sci., XLI-B3, 701, 10.5194/isprsarchives-XLI-B3-701-2016 · DOI
  52. Stoica, 2004, A Gibbs point process for road extraction from remotely sensed images, Int. J. Comput. Vis., 57, 121, 10.1023/B:VISI.0000013086.45688.5d · DOI
  53. Stoica, 2007, A three-dimensional object point process for detection of cosmic filaments, J. Roy. Stat. Soc. Ser. C: Appl. Stat., 56, 459, 10.1111/j.1467-9876.2007.00587.x · DOI
  54. Tournaire, 2010, An efficient stochastic approach for building footprint extraction from digital elevation models, ISPRS J. Photogram. Remote Sensing, 65, 317, 10.1016/j.isprsjprs.2010.02.002 · DOI
  55. Tupin, 1998, Detection of linear features in SAR images: application to road network extraction, IEEE Trans. Geosci. Remote Sensing, 36, 434, 10.1109/36.662728 · DOI
  56. Verdié, 2014, Detecting parametric objects in large scenes by Monte Carlo sampling, Int. J. Comput. Vis., 106, 57, 10.1007/s11263-013-0641-0 · DOI
  57. Vetter, 2014, Modification of high resolution airborne laser scanning DTMs for drainage network delineation, Photogram. Fernerkundung Geoinform., 1, 41, 10.1127/1432-8364/2014/0208 · DOI
  58. Wegner, 2015, Road networks as collections of minimum cost paths, ISPRS J. Photogram. Remote Sensing, 108, 128, 10.1016/j.isprsjprs.2015.07.002 · DOI
  59. Wilson, 2008, Water in the landscape: a review of contemporary flow routing algorithms, 213
  60. Zhang, 2004, Towards an operational system for automated updating of road databases by integration of imagery and geodata, ISPRS J. Photogram. Remote Sensing, 58, 166, 10.1016/j.isprsjprs.2003.09.004 · DOI

Cited by

Sorted by citations

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

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review