yea, thanks :D , I used a tiny idea from geoguessing, that I banded the search on islands only in latitude between -30 to +30 deg. based on the sky and the tropical vibes in the img , and it worked !

agree! AWESOME work!

It’s an effective a surprisingly old technique, being used on cruise missiles as early as the 1960s. It actually precedes GPS and satellite navigation by several decades. Im continuously blown away by what engineers were able to do in that era with such limited computing power. Take a look at SAGE, for example.

Fun fact: the usage of TERCOM in the tomahawk missile actually limited its ability to be used in Operation Desert Storm. Routes had to be planned to go around actual topographical features, instead of hundreds of miles of flat desert.

oh, wow, I didnt know that existed, thank u, sure gonna look into it

omg wow, thats super hard, although cool ,

Claude / Gemini + OSM Turbo is a crazy you can do natural language queries like "find me a bus stop in germany that's surrounded by more than 5 three story buildings"

yea , heard about them before, but didnt know that whole treasure till I really used it , impressive

Weirdly enough, I'm working on a similar system for position tracking in canyons. It's hybrid, uses a combination of Kalman filters, particle filters and GPS (EDIT: and LIDAR based DEM) and is based on the obvious (in hindsight) realisation that the view of the sky to get an accurate gps fix is inversely proportional to the constraints of the terrain. If you have a low field of view of the sky, you can use sensor data to constrain your likely position. I should have hardware samples for testing in the next month or so. Hopefully my theory stands up!

I don't see it, did he delete it?

EVERY technology could be used by a police state

I tried to use the sun info , but honestly I couldn't at all,

thx for the tip

I meant the blog itself, the writeup, the steps and the walkthrough all by hand , the final code u see is llm refined, of course, I wont publish my messy and spaghetti files with much tests, failures and dead ends, also vizualizations functions to produce that green maps , and faulty versions of them

but you are right, I should add that

"No EXIF, no GPS, no camera make or model."

Yeah, a human definitely wrote this. Nothing fishy here. (Why would the camera make or model matter???)

thanks, appreciate it

thanks, and yea, it should be solved easily by passing the img to google lens, the website is the first result, but I found a fun opportunity to solve it in different way

errors = llm, no errors = llm, any word from a list of hundreds = llm, absence of any llm-words = suspiciously like an llm instructed not to use those words, declare no llm was used = llm.

there is no winning. if you post something in 2026 or beyond, someone is going to exclaim "llm!". i feel badly for aspiring bloggers or writers. it's also getting rather annoying that 50% of comments on hn, regardless of the topic they are posted on, are the exact same comment about llms.

haha : "write like a non-native English speaker"

man, Im actually non native speaker xDD

"replace you for u" ???? what ?!

yea, good observation, my guess is its the data more than the filter. OSM coastline polygons are generalized to different degrees depending on who traced them and from what imagery, so the fine shape detail a halo check would key on often is not in the geometry at all.

I observed that at the end, didnt push on it further though. It already passed and I was super exhausted

thaaank you !! Its my first ever challenge to do, and yea, I really found my passion

I have no idea about that particular company, but wouldn't satellite-based synthetic aperture radar datasets make this "super easy?" I would imagine so.

https://en.wikipedia.org/wiki/Synthetic-aperture_radar

https://eos.com/blog/what-is-sar-synthetic-aperture-radar-im...

Assuming they (and militaries broadly) do this +more, like actually using vision models trained on billions of geolocated landscape photos.

thanks ! no idea about Palantir, but in my opinion, this can not be automated , needs much manual work and tons of trial and error

thaaank u man, I really appreciate ur comment

glad u liked it :D

really glad that you liked it

haha, thanks :D I was hesitant to whether write it or not, but I really really despise llm generated posts and blogs and im glad someone appreciated it

do u mean the whole work ? I spent at first 3 "whole" days in research, trial and error trying different methods and scripts, like for example tried the depth estimation to build upon it, failed many times till I gave up then came back after a week and spent another 4 days till succeeded then the refining, cleaning and organizing of all of that, also structuring and writing the blog, took about another 3 days

you can say that total is ~10 days of work

honestly, I didn't think about it, I just trusted the OSM polygons

thannks, really grateful :D

haha, I actually agree

yea, search about geoguessing on youtube, people like Rainbolt, https://www.youtube.com/@georainbolt

they literally memorize and get patterns of every possible road, place, map of any area (scanned by google earth), getting exact coordinates from single image, and play competitions and world cup based on that

they do really nice videos about finding places in old photos people ask for

haha, I wish , this is my first OSINT challenge to solve tho

All of this to try and learn something new