Geolocating a random island using geometry and CUDA programming

226 pointsposted 4 hours ago
by yassa9

46 Comments

NKosmatos

3 hours ago

Excellent write up and an enjoyable read! Reminds me of the “good old times” where posts on HN were written by humans and with a specific writing style like yours. You could’ve used a little bit more of geoguessing to narrow down results, or do a brute force visual check on the last hundred or so ;-)

yassa9

3 hours ago

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 !

bmurray7jhu

3 hours ago

For drones and missiles, this technique is known as Terrain Contour Matching. If terrain contour are measured optically, navigation is independent of RF jamming, unlike GNSS.

https://en.wikipedia.org/wiki/TERCOM

openasocket

25 minutes ago

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.

yassa9

3 hours ago

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

aquafox

4 minutes ago

Nice, but Rainbolt would do it in under a minute ;)

yassa9

3 minutes ago

haha, I actually agree

o4c

2 hours ago

Really great article! OP, you did an awesome job breaking down a complex problem into manageable chunks and synthesizing the solution.

yassa9

2 hours ago

thanks, appreciate it

lexlambda

4 hours ago

OpenStreetMap data really is a godsend for such OSINT purposes. Works much better in populated areas too, with more features like roads, shops, electric lines that can be used to search.

GaryNumanVevo

2 hours ago

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"

yassa9

4 hours ago

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

naniel

27 minutes ago

this is really cool. fun little problem turned into great write-up, and i love that you included the code snippets. thanks for sharing

yassa9

23 minutes ago

really glad that you liked it

ImJasonH

2 hours ago

Excellent read, I loved it.

Incidentally, the image seems to be the one the resort uses on their website! https://oanresort.wixsite.com/chuuk

yassa9

2 hours ago

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

num42

2 hours ago

Good article! Off-topic, Is Palantir doing the same thing with its internal software to geolocate?

yassa9

an hour ago

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

cecinuga

4 hours ago

I read all the process, literally awesome, i don't do OSINT (i know only what is this) and i think that's very cool

yassa9

4 hours ago

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

bitcurious

3 hours ago

It’s interesting that most top contenders don’t pass the eyeball halo check, seems like there’s room to optimize that filter in code.

yassa9

3 hours ago

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

ape4

3 hours ago

What about tides? Would the outline of the island be different based on the time of day.

yassa9

2 hours ago

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

hhh

4 hours ago

great blog and great writeup

yassa9

4 hours ago

thannks, really grateful :D

piterrro

4 hours ago

really impressive, could that be the way to locate yourself without GPS? assuming we know more/less where we are

yassa9

3 hours ago

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

phalanxx

3 hours ago

What do you mean by no LLM generation if an LLM did all the coding based on reading through the .py files? Pangram isn't kind to "your" text either.

yassa9

3 hours ago

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

StilesCrisis

2 hours ago

Just by reading your actual messages it's easy to see that you didn't write the blog post entirely by hand.

StilesCrisis

2 hours ago

"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???)

voidUpdate

2 hours ago

If you know the camera make and model, you might be able to get lens parameters and get better estimates of real world geometry from the image

yassa9

2 hours ago

yea thank u, that's another part, but mainly it would hard although knowing that, because you need to know elevation of the drone or the camera, which is also extremely difficult (I already mentioned that in the blog)

StilesCrisis

2 hours ago

The camera make and model wouldn't tell you the lens parameters. The EXIF would, but that was already covered in the triplet.

yassa9

2 hours ago

ok, if u came with the whole conclusion by only this line, ok , but to answer u, ( I hate to justify myself , but have to ) I started writing the blog after I started solving another challenge from gralhix : https://gralhix.com/list-of-osint-exercises/osint-exercise-0...

and the part of the solution came from the metadata, the camera model, you can check urself, so when I came back to write the blog, it just came by flow,

ohyoutravel

4 hours ago

> NOTE: this is a genuine human work, didnt use LLM generation.

A million upvotes from me.

yassa9

3 hours ago

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

ligarota

22 minutes ago

All of this to not use Google images

melozo

15 minutes ago

All of this to try and learn something new