dorsal/arxiv
View SchemaDiffusion-based method for producing density equalizing maps
| Authors | Michael T. Gastner, M. E. J. Newman |
|---|---|
| Categories | |
| ArXiv ID | physics/0401102 |
| URL | https://arxiv.org/abs/physics/0401102 |
| DOI | 10.1073/pnas.0400280101 |
| Journal | Proc. Natl. Acad. Sci. USA 101, 7499-7504 (2004) |
Abstract
Map makers have long searched for a way to construct cartograms -- maps in which the sizes of geographic regions such as countries or provinces appear in proportion to their population or some other analogous property. Such maps are invaluable for the representation of census results, election returns, disease incidence, and many other kinds of human data. Unfortunately, in order to scale regions and still have them fit together, one is normally forced to distort the regions' shapes, potentially resulting in maps that are difficult to read. Many methods for making cartograms have been proposed, some of them extremely complex, but all suffer either from this lack of readability or from other pathologies, like overlapping regions or strong dependence on the choice of coordinate axes. Here we present a new technique based on ideas borrowed from elementary physics that suffers none of these drawbacks. Our method is conceptually simple and produces useful, elegant, and easily readable maps. We illustrate the method with applications to the results of the 2000 US presidential election, lung cancer cases in the State of New York, and the geographical distribution of stories appearing in the news.
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"abstract": "Map makers have long searched for a way to construct cartograms -- maps in\nwhich the sizes of geographic regions such as countries or provinces appear in\nproportion to their population or some other analogous property. Such maps are\ninvaluable for the representation of census results, election returns, disease\nincidence, and many other kinds of human data. Unfortunately, in order to scale\nregions and still have them fit together, one is normally forced to distort the\nregions\u0027 shapes, potentially resulting in maps that are difficult to read. Many\nmethods for making cartograms have been proposed, some of them extremely\ncomplex, but all suffer either from this lack of readability or from other\npathologies, like overlapping regions or strong dependence on the choice of\ncoordinate axes. Here we present a new technique based on ideas borrowed from\nelementary physics that suffers none of these drawbacks. Our method is\nconceptually simple and produces useful, elegant, and easily readable maps. We\nillustrate the method with applications to the results of the 2000 US\npresidential election, lung cancer cases in the State of New York, and the\ngeographical distribution of stories appearing in the news.",
"arxiv_id": "physics/0401102",
"authors": [
"Michael T. Gastner",
"M. E. J. Newman"
],
"categories": [
"physics.data-an",
"physics.soc-ph"
],
"doi": "10.1073/pnas.0400280101",
"journal_ref": "Proc. Natl. Acad. Sci. USA 101, 7499-7504 (2004)",
"title": "Diffusion-based method for producing density equalizing maps",
"url": "https://arxiv.org/abs/physics/0401102"
},
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