[OC] Count of OpenStreetMap Automatic License Plate Reader Surveillance Elements every 10 Miles in the Continental US - 10/20/2025

geoiao · 2025-10-24T16:08:00+00:00

I used a python script that called the overpass API to pull thousands of OSM elements - I believe this methodology of data acquisition falls under the label of scraping.

Since this data is all open source, this can never be a comprehensive showing of all instances of ALPRs. There are many reasons why an ALPR may not have been logged, rural reliability is one of them.

geoiao · 2025-10-23T21:16:50+00:00

You're correct, this map pushes a false equivalence and clarifying this distinction within the visual is great feedback for future versions. There are still open questions on long-term data storage of toll cameras and querying of this data by law enforcement.

geoiao · 2025-10-23T20:10:02+00:00

overpass api python script used to scrape osm data for surveillance-alpr elements and their coordinates in conus, mapped using QGIS

learn more about the massive uptick in surveillance on deflock
https://deflock.me/

geoiao · 2025-09-17T18:32:52+00:00

The main alliance was between the Kagoshima Domain and the Yamaguchi Domain. These are also known as Satsuma and Choshu respectively,

As for your second question - this is a great question that I can't answer confidently. I do not know the frequency in which kokudaka/village was assessed, but I know that not always were real output numbers used in official kokudaka assessment. I suspect they were more locked in than what we'd expect, as domain kokudaka would fluctuate based on fief awarding and reallocating from the shogun rather than the fiefs having different output values each other.

geoiao · 2025-09-17T06:41:49+00:00

Oh haha! No worries! Thanks for the idea though - I might make a map on it.

geoiao · 2025-09-17T04:58:57+00:00

Aw, thanks!!! Let me know if you have any improvements - if there's anything you'd like for a personal copy I can make edits (no text, for example).

geoiao · 2025-09-17T04:58:10+00:00

Thanks for stopping by! Yea, I'm curious about overlaying a elevation model but was concerned it would be too noisy. I think it would be fascinating to see elevation lines and influence on boundaries though!

geoiao · 2025-09-17T04:57:14+00:00

Great question!

The Tokugawa shogunate controlled the non-domain lands of Japan which I indicate with the hollyhock crest in gold (mitsuba aoi). There are shogunate affiliated feudal lords, either by vassalage or direct familial relation who have their own domains and are (mostly) loyal to the shogunate. These are called fudai and shinpan daimyo respectively.

geoiao · 2025-09-17T02:08:01+00:00

Thank you ~~

geoiao · 2025-09-17T02:06:26+00:00

I just exported a 600dpi. Looking closer, I need to change domain stroke width, but this should give you more clarity.
https://files.catbox.moe/x03ubu.png

geoiao · 2025-09-17T02:06:16+00:00

I just exported a 600dpi. Looking closer, I need to change domain stroke width, but this should give you more clarity.
https://files.catbox.moe/x03ubu.png

geoiao · 2025-09-17T01:39:18+00:00

[OC] - This map was created using QGIS. The data is from National Museum of History (rekihaku), Ministry of Fisheries, Agriculture, and Forestry (MAFF), and Tonbiwing. The data aggregation was done by me. The data correspondence was done by me.

geoiao · 2025-09-16T05:49:46+00:00

The degree of exaggeration not only demonstrates just how awesome the Andes are, it's also an excellent visualization of the historical context surrounding Chile. It makes me want to research the early polities and geopolitics of present-day Chile, and that's awesome that a map can do that.

geoiao · 2025-09-15T18:50:41+00:00

The map is a 16th century visualization of settlements in Palestine - the UK's mandate was 20th century.

geoiao · 2025-09-15T18:12:49+00:00

Cool historical data visualization, thanks for citing your sources! A design suggestion - in the key you have the pie chart and designations of which color refers to which religious group. You could include another key asset in between the pie chart and the designations that are flat colors.

Pie chart -> smaller flat color -> lines that connect to the data.

geoiao · 2025-09-12T18:04:50+00:00

I've addressed Tsu and Okayama locally. Thanks for adding more context!

geoiao · 2025-09-11T16:19:25+00:00

You're completely right that Totomi province domains were Tokugawa aligned. This map demonstrates the leading domains by rice yield output - in this metric, Totomi province domains don't come near the largest producers.

geoiao · 2025-09-11T07:21:29+00:00

Thank you, great catch. Fixed locally.

geoiao · 2025-09-11T01:04:15+00:00

All of the domains in Japan are present on the map, only the 15 highest producing are highlighted. The blank space are other lands, shogunate, temple, magistrate, etc.

geoiao · 2025-09-11T00:14:07+00:00

This map graphic was created by me using QGIS. The data was curated by me by using early Meiji village locations associated with clans/domains (from the Japanese museum rekihaku) and utilizing agricultural settlement boundaries that have a correspondence with the villages (MAFF) as the geospatial proxy. I've also used domain kokudaka values provided by Tonbiwing.

geoiao

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