{"id":467,"date":"2007-07-12T20:08:00","date_gmt":"2007-07-12T20:08:00","guid":{"rendered":"http:\/\/scientopia.org\/blogs\/goodmath\/2007\/07\/12\/fractal-borders\/"},"modified":"2018-11-27T20:20:03","modified_gmt":"2018-11-28T01:20:03","slug":"fractal-borders","status":"publish","type":"post","link":"http:\/\/www.goodmath.org\/blog\/2007\/07\/12\/fractal-borders\/","title":{"rendered":"Fractal Borders"},"content":{"rendered":"

Part of what makes fractals so fascinating is that in addition to being beautiful, they also describe real things – they’re genuinely useful and important for helping us to describe and understand the world around us. A great example of this is maps and measurement.<\/p>\n

Suppose you want to measure the length of the border between Portugal and Spain. How long is it? You’d think that that’s a straightforward question, wouldn’t you?<\/p>\n

It’s not. Spain and Portugal have a natural border, defined by geography. And in Portuguese books, the length of that border has been measured as more than 20% longer than it has in Spanish books. This difference has nothing to do with border conflicts or disagreements about where the border lies. The difference comes from the structure<\/em> of the border, and way that it gets measured.<\/p>\n

Natural structures don’t measure the way that we might like them to. Imagine that you walked the border between Portugal and Spain using a pair of chained flags like they use to mark the down in football – so you’d be measuring the border on 10 yard line segments. You’ll get one measure of the length of the border, we’ll call it Lyards<\/sub><\/p>\n

Now, imagine that you did the same thing, but instead of using 10 yard segments, you used 10 foot segments – that is, segments 1\/3 the length. You won’t<\/em> get the same length; you’ll get a different length, Lfeet<\/sub>.<\/p>\n

Then do it again, but with a rope 10 inches long. You’ll get a *third* length, Linches<\/sub>.<\/p>\n

Linches<\/sub> will be greater than Lfeet<\/sub>, which will be greater that Lyards<\/sub>.<\/p>\n

\"border.jpg\"<\/p>\n

The problem is that the border isn’t smooth, it isn’t a differentiable curve. As you move to progressively smaller scales, the border features progressively smaller features. At a 10 mile scale, you’ll be looking at features like valleys, rivers, cliffs, etc, and defining the precise border in terms of those. But when you go to the ten-yard scale, you’ll find that the valleys divide into foothills, and the border line should wind between hills. Get down to the ten-foot scale, and you’ll start noticing boulders, jags in the lines, twists in the river. Go down to the 10-inch scale, and you’ll start noticing rocks, jagged shapes. By this point, rivers will have ceased to appear as lines, but they’ll be wide bands, and if you want to find the middle, you’ll need to look at the shapes of the banks, which are irregular and jagged down to the millimeter scale. The diagram above shows a simple example of what I mean – it starts with a real clip taken from a map of the border, and then shows two possible zooms of that showing more detail at smaller scales.<\/p>\n

The border is fractal. If you try to measure its dimension, topologically, it’s one-dimension – the line of the border. But if you look at its dimension metrically, and compute its Hausdorff dimension, you’ll find that it’s not 2, but it’s a lot more than 1.<\/p>\n

Shapes like this really are fractal. To give you an idea – which of the two photos below is real, and which is generated using a fractal equation?<\/p>\n

\"sharpestp.jpg\"
\n\"arizona4_640.jpg\"<\/p>\n","protected":false},"excerpt":{"rendered":"

Part of what makes fractals so fascinating is that in addition to being beautiful, they also describe real things – they’re genuinely useful and important for helping us to describe and understand the world around us. A great example of this is maps and measurement. Suppose you want to measure the length of the border […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[86],"tags":[],"class_list":["post-467","post","type-post","status-publish","format-standard","hentry","category-fractals"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p4lzZS-7x","jetpack_sharing_enabled":true,"jetpack_likes_enabled":true,"_links":{"self":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/467","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/comments?post=467"}],"version-history":[{"count":2,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/467\/revisions"}],"predecessor-version":[{"id":3666,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/posts\/467\/revisions\/3666"}],"wp:attachment":[{"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/media?parent=467"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/categories?post=467"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.goodmath.org\/blog\/wp-json\/wp\/v2\/tags?post=467"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}