The DOI matches its Crossref record.
A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic
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Citations
Cited by
An evaluation of void‐filling interpolation methods for SRTM data
Reuter, H. I., Nelson, A., & Jarvis, A. (2007) · International Journal of Geographical Information Science · doi:10.1080/13658810601169899 · Cited by 915
César Izaurralde, R., Rosenberg, N. J., & Lal, R. (2001) · Advances in Agronomy · doi:10.1016/s0065-2113(01)70003-x · Cited by 107
Nature and Aims of Geomorphological Mapping
Dramis, F., Guida, D., & Cestari, A. (2011) · Developments in Earth Surface Processes · doi:10.1016/b978-0-444-53446-0.00003-3 · Cited by 76
Semantic calibration of digital terrain analysis scale
Miller, B. A. (2014) · Cartography and Geographic Information Science · doi:10.1080/15230406.2014.883488 · Cited by 23
Shim, W. J., Ko, I., & Park, S. J. (2022) · Journal of Computer Applications in Archaeology · doi:10.5334/jcaa.97 · Cited by 2
Metadata
- Authors
- MacMillan, R. A., Pettapiece, W. W., Nolan, S. C., & Goddard, T. W.
- Venue
- Fuzzy Sets and Systems
- Publisher
- Elsevier BV
- Published
- 2000-07
- Volume
- 113
- Issue
- 1
- Pages
- 81-109
- ISSN
- 0165-0114 (ISSN-L)
- OpenAlex
- W1972819089
- Cited by
- 340
- References
- 0
- FWCI
- 8.72
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. https://app.cochat.ai/papers/10.1016/s0165-0114(99)00014-7
- The paper
- MacMillan, R. A., Pettapiece, W. W., Nolan, S. C., & Goddard, T. W. (2000). A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Sets and Systems. https://doi.org/10.1016/s0165-0114(99)00014-7
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.