The DOI matches its Crossref record.
A global, self‐consistent, hierarchical, high‐resolution shoreline database
Abstract
We present a high‐resolution shoreline data set amalgamated from two databases in the public domain. The data have undergone extensive processing and are free of internal inconsistencies such as erratic points and crossing segments. The shorelines are constructed entirely from hierarchically arranged closed polygons. The data can be used to simplify data searches and data selections or to study the statistical characteristics of shorelines and landmasses. The data set can be accessed both electronically over Internet and from the National Geophysical Data Center, Boulder, Colorado; it comes with access software and routines to facilitate decimation based on a standard line‐reduction algorithm.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Hartmann, J., & Moosdorf, N. (2012) · Geochemistry, Geophysics, Geosystems · doi:10.1029/2012gc004370 · Cited by 1,159
Sea Level Rise and Implications for Low-Lying Islands, Coasts and Communities
(2022) · The Ocean and Cryosphere in a Changing Climate · doi:10.1017/9781009157964.012 · Cited by 831
Vulnerability of coastal aquifers to groundwater use and climate change
Ferguson, G., & Gleeson, T. (2012) · Nature Climate Change · doi:10.1038/nclimate1413 · Cited by 708
Three decades of high-resolution coastal sea surface temperatures reveal more than warming
Lima, F. P., & Wethey, D. S. (2012) · Nature Communications · doi:10.1038/ncomms1713 · Cited by 549
Robustness and uncertainties in global multivariate wind-wave climate projections
Morim, J., Hemer, M., Wang, X. L., Cartwright, N., Trenham, C., Semedo, A., Young, I., Bricheno, L., Camus, P., Casas-Prat, M., et al. (2019) · Nature Climate Change · doi:10.1038/s41558-019-0542-5 · Cited by 384
Metadata
- Authors
- Wessel, P., & Smith, W. H. F.
- Venue
- Journal of Geophysical Research: Solid Earth
- Publisher
- American Geophysical Union (AGU)
- Published
- 1996-04-10
- Volume
- 101
- Issue
- B4
- Pages
- 8741-8743
- ISSN
- 0148-0227 (ISSN-L)
- OpenAlex
- W2159400622
- Cited by
- 1,575
- References
- 0
- FWCI
- 8.82
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A global, self‐consistent, hierarchical, high‐resolution shoreline database. https://app.cochat.ai/papers/10.1029/96jb00104
- The paper
- Wessel, P., & Smith, W. H. F. (1996). A global, self‐consistent, hierarchical, high‐resolution shoreline database. Journal of Geophysical Research: Solid Earth. https://doi.org/10.1029/96jb00104
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.
