{"id":6380,"date":"2017-09-18T07:53:14","date_gmt":"2017-09-18T12:53:14","guid":{"rendered":"https:\/\/rud.is\/b\/?p=6380"},"modified":"2022-08-05T19:40:52","modified_gmt":"2022-08-06T00:40:52","slug":"mapping-fall-foliage-with-sf","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2017\/09\/18\/mapping-fall-foliage-with-sf\/","title":{"rendered":"Mapping Fall Foliage with sf"},"content":{"rendered":"<p>I was socially engineered by @yoniceedee into creating today&#8217;s post due to being prodded with this tweet:<\/p>\n<blockquote class=\"twitter-tweet\" data-lang=\"en\">\n<p lang=\"en\" dir=\"ltr\">Where to see the best fall foliage, based on your location: <a href=\"https:\/\/t.co\/12pQU29ksB\">https:\/\/t.co\/12pQU29ksB<\/a> <a href=\"https:\/\/t.co\/JiywYVpmno\">pic.twitter.com\/JiywYVpmno<\/a><\/p>\n<p>&mdash; Vox (@voxdotcom) <a href=\"https:\/\/mobile.twitter.com\/voxdotcom\/status\/909729977633050624\">September 18, 2017<\/a><\/p><\/blockquote>\n<p><script async src=\"\/\/platform.twitter.com\/widgets.js\" charset=\"utf-8\"><\/script><\/p>\n<p>Since there aren&#8217;t nearly enough <code>sf<\/code> and <code>geom_sf<\/code> examples out on the wild, wild <a rel=\"tag\" class=\"hashtag u-tag u-category\" href=\"https:\/\/rud.is\/b\/tag\/rstats\/\">#rstats<\/a> web, here&#8217;s a short one that shows how to do basic <code>sf<\/code> operations, including how to plot <code>sf<\/code> objects in ggplot2 and animate a series of them with <code>magick<\/code>.<\/p>\n<p>I&#8217;m hoping someone riffs off of this to make an interactive version with Shiny. If you do, definitely drop a link+note in the comments!<\/p>\n<p>(If folks want some exposition here, let me know in the comments and I&#8217;ll rig up an R Markdown document with more step-by-step details.)<\/p>\n<p>Full RStudio project file (with pre-cached data) is <a href=\"https:\/\/github.com\/hrbrmstr\/foliage\">on GitHub<\/a>.<\/p>\n<p><a href=\"https:\/\/i0.wp.com\/rud.is\/dl\/foliage.gif?ssl=1\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" src=\"https:\/\/i0.wp.com\/rud.is\/dl\/foliage.gif?resize=510%2C306&#038;ssl=1\" width=\"510\" height=\"306\" class=\"size-full\" \/><\/a><\/p>\n<pre><code class=\"language-r\">library(rprojroot)\nlibrary(sf)\nlibrary(magick)\nlibrary(tidyverse) # NOTE: Needs github version of ggplot2\n\nroot &lt;- find_rstudio_root_file()\n\n# \"borrow\" the files from SmokyMountains.com, but be nice and cache them to\n# avoid hitting their web server for every iteration\n\nc(\"https:\/\/smokymountains.com\/wp-content\/themes\/smcom-2015\/to-delete\/js\/us.json\",\n  \"https:\/\/smokymountains.com\/wp-content\/themes\/smcom-2015\/js\/foliage2.tsv\",\n  \"https:\/\/smokymountains.com\/wp-content\/themes\/smcom-2015\/js\/foliage-2017.csv\") %&gt;%\n  walk(~{\n    sav_tmp &lt;- file.path(root, \"data\", basename(.x))\n    if (!file.exists(sav_tmp)) download.file(.x, sav_tmp)\n  })\n\n# next, we read in the GeoJSON file twice. first, to get the counties\nstates_sf &lt;- read_sf(file.path(root, \"data\", \"us.json\"), \"states\", stringsAsFactors = FALSE)\n\n# we only want the continental US\nstates_sf &lt;- filter(states_sf, !(id %in% c(\"2\", \"15\", \"72\", \"78\")))\n\n# it doesn't have a CRS so we give it one\nst_crs(states_sf) &lt;- 4326\n\n# I ran into hiccups using coord_sf() to do this, so we convert it to Albers here\nstates_sf &lt;- st_transform(states_sf, 5070)\n\n\n# next we read in the states\ncounties_sf &lt;- read_sf(file.path(root, \"data\", \"us.json\"), \"counties\", stringsAsFactors = FALSE)\nst_crs(counties_sf) &lt;- 4326\ncounties_sf &lt;- st_transform(counties_sf, 5070)\n\n# now, we read in the foliage data\nfoliage &lt;- read_tsv(file.path(root, \"data\", \"foliage-2017.csv\"),\n                    col_types = cols(.default=col_double(), id=col_character()))\n\n# and, since we have a lovely sf tidy data frame, bind it together\nleft_join(counties_sf, foliage, \"id\") %&gt;%\n  filter(!is.na(rate1)) -&gt; foliage_sf\n\n# now, we do some munging so we have better labels and so we can\n# iterate over the weeks\ngather(foliage_sf, week, value, -id, -geometry) %&gt;%\n  mutate(value = factor(value)) %&gt;%\n  filter(week != \"rate1\") %&gt;%\n  mutate(week = factor(week,\n                       levels=unique(week),\n                       labels=format(seq(as.Date(\"2017-08-26\"),\n                                         as.Date(\"2017-11-11\"), \"1 week\"),\n                                     \"%b %d\"))) -&gt; foliage_sf\n\n# now we make a ggplot object for each week and save it out to a png\npb &lt;- progress_estimated(nlevels(foliage_sf$week))\nwalk(1:nlevels(foliage_sf$week), ~{\n\n  pb$tick()$print()\n\n  xdf &lt;- filter(foliage_sf, week == levels(week)[.x])\n\n  ggplot() +\n    geom_sf(data=xdf, aes(fill=value), size=0.05, color=\"#2b2b2b\") +\n    geom_sf(data=states_sf, color=\"white\", size=0.125, fill=NA) +\n    viridis::scale_fill_viridis(\n      name=NULL,\n      discrete = TRUE,\n      labels=c(\"No Change\", \"Minimal\", \"Patchy\", \"Partial\", \"Near Peak\", \"Peak\", \"Past Peak\"),\n      drop=FALSE\n    ) +\n    labs(title=sprintf(\"Foliage: %s \", unique(xdf$week))) +\n    ggthemes::theme_map() +\n    theme(panel.grid=element_line(color=\"#00000000\")) +\n    theme(panel.grid.major=element_line(color=\"#00000000\")) +\n    theme(legend.position=\"right\") -&gt; gg\n\n  ggsave(sprintf(\"%02d.png\", .x), gg, width=5, height=3)\n\n})\n\n# we read them all back in and animate the foliage\nsprintf(\"%02d.png\", 1:nlevels(foliage_sf$week)) %&gt;%\n  map(image_read) %&gt;%\n  image_join() %&gt;%\n  image_animate(1)\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"<p>I was socially engineered by @yoniceedee into creating today&#8217;s post due to being prodded with this tweet: Where to see the best fall foliage, based on your location: https:\/\/t.co\/12pQU29ksB pic.twitter.com\/JiywYVpmno &mdash; Vox (@voxdotcom) September 18, 2017 Since there aren&#8217;t nearly enough sf and geom_sf examples out on the wild, wild #rstats web, here&#8217;s a short [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":6382,"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,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[753,91],"tags":[810],"class_list":["post-6380","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ggplot","category-r","tag-post"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Mapping Fall Foliage with sf - rud.is<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rud.is\/b\/2017\/09\/18\/mapping-fall-foliage-with-sf\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Mapping Fall Foliage with sf - rud.is\" \/>\n<meta property=\"og:description\" content=\"I was socially engineered by @yoniceedee into creating today&#8217;s post due to being prodded with this tweet: Where to see the best fall foliage, based on your location: https:\/\/t.co\/12pQU29ksB pic.twitter.com\/JiywYVpmno &mdash; 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This year, we have Quarto, and it comes with so many batteries included that you'd think it was Christmas. One of those batteries is full support for the Observable runtime.\u2026","rel":"","context":"In &quot;d3&quot;","block_context":{"text":"d3","link":"https:\/\/rud.is\/b\/category\/d3\/"},"img":{"alt_text":"foliage map","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2022\/09\/foliage.png?fit=1200%2C1040&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2022\/09\/foliage.png?fit=1200%2C1040&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2022\/09\/foliage.png?fit=1200%2C1040&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2022\/09\/foliage.png?fit=1200%2C1040&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2022\/09\/foliage.png?fit=1200%2C1040&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":11612,"url":"https:\/\/rud.is\/b\/2018\/10\/10\/geojson-version-of-cbc-quebec-ridings-hex-cartograms-with-example-usage-in-r\/","url_meta":{"origin":6380,"position":1},"title":"GeoJSON  Version of CBC Quebec Ridings Hex Cartograms with  Example Usage in R","author":"hrbrmstr","date":"2018-10-10","format":false,"excerpt":"The CBC covered the recent (as of the original post-time on this blog entry) Quebec elections and used a well-crafted hex grid map to display results: They have a great 'splainer on why they use this type of map. Thinking that it may be useful for others, I used a\u2026","rel":"","context":"In &quot;cartography&quot;","block_context":{"text":"cartography","link":"https:\/\/rud.is\/b\/category\/cartography\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2018\/10\/ggplot-sf.png?fit=1200%2C900&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2018\/10\/ggplot-sf.png?fit=1200%2C900&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2018\/10\/ggplot-sf.png?fit=1200%2C900&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2018\/10\/ggplot-sf.png?fit=1200%2C900&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2018\/10\/ggplot-sf.png?fit=1200%2C900&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":12667,"url":"https:\/\/rud.is\/b\/2020\/03\/02\/make-wsj-esque-uber-tuesday-democrat-delegate-cartograms-in-r-with-catchpole\/","url_meta":{"origin":6380,"position":2},"title":"Make WSJ-esque \u00dcber Tuesday Democrat Delegate Cartograms in R with {catchpole}","author":"hrbrmstr","date":"2020-03-02","format":false,"excerpt":"For folks who are smart enough not to go near Twitter, I've been on a hiatus from the platform insofar as reading the Twitter feed goes. \"Why\" isn't the subject of this post so I won't go into it, but I've broken this half-NYE resolution on more than one occasion\u2026","rel":"","context":"In &quot;R&quot;","block_context":{"text":"R","link":"https:\/\/rud.is\/b\/category\/r\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2020\/03\/my-map-2.png?fit=1200%2C784&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2020\/03\/my-map-2.png?fit=1200%2C784&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2020\/03\/my-map-2.png?fit=1200%2C784&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2020\/03\/my-map-2.png?fit=1200%2C784&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2020\/03\/my-map-2.png?fit=1200%2C784&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":14337,"url":"https:\/\/rud.is\/b\/2023\/09\/09\/foliage-2023\/","url_meta":{"origin":6380,"position":3},"title":"Foliage 2023","author":"hrbrmstr","date":"2023-09-09","format":false,"excerpt":"2023-09-10 UPDATE: Art Steinmetz took me up on the Shiny challenge (at the end of the post) and did a fantastic job! The days are getting shorter and when we were visiting Down East Maine the other week, there was just a hint of some trees starting to change up\u2026","rel":"","context":"In &quot;data wrangling&quot;","block_context":{"text":"data wrangling","link":"https:\/\/rud.is\/b\/category\/data-wrangling\/"},"img":{"alt_text":"conus foliage map 2023","src":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2023\/09\/lit-plot.png?fit=1200%2C1137&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2023\/09\/lit-plot.png?fit=1200%2C1137&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2023\/09\/lit-plot.png?fit=1200%2C1137&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2023\/09\/lit-plot.png?fit=1200%2C1137&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/rud.is\/b\/wp-content\/uploads\/2023\/09\/lit-plot.png?fit=1200%2C1137&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":13232,"url":"https:\/\/rud.is\/b\/2021\/11\/02\/30daymapchallenge-2021-day-2-lines\/","url_meta":{"origin":6380,"position":4},"title":"#30DayMapChallenge 2021 Day 2: Lines","author":"hrbrmstr","date":"2021-11-02","format":false,"excerpt":"The 30-Day Map Challenge is on again, and I'm hoping to be able to scrounge some time to get an entry for each day. Day 2 is lines (Day 1 was posted on Twitter only) and \u2014 while I'm hoping to focus on saving U.S. democracy for the majority of\u2026","rel":"","context":"In &quot;gis&quot;","block_context":{"text":"gis","link":"https:\/\/rud.is\/b\/category\/gis\/"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":12195,"url":"https:\/\/rud.is\/b\/2019\/05\/18\/mapping-tornado-alley-with-r\/","url_meta":{"origin":6380,"position":5},"title":"Mapping Tornado Alley with R","author":"hrbrmstr","date":"2019-05-18","format":false,"excerpt":"I caught a re-tweet of this tweet by @harry_stevens: THREAD: I wrote a post on @observablehq about a map I made today. 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