2
points
zetalemur
Joined 47 karma
Hey fellow HNer. :)
E-Mail:
$ echo aG5AemV0YWxhYnMuaW8K | base64 -d
Happy coding
Founder and CTO of ζLabs
https://www.zetalabs.io
- Interesting read - there's a lot of progress in the open map styling scene and OSM maps with good data can make amazing maps and it has many different features [0].
It's also interesting to make maps directly from raw data (in this case that would be aerial imagery with mostly elevation data). E.g. if you find good training data you can easily make "land-cover" maps and although my example (of Austria) [1] does not have annotations (addresses, etc.), it's still nice to look at and has the benefit of being extremely compressible (compared to aerial raw imagery).
[0] https://wiki.openstreetmap.org/wiki/Map_features [1] https://turmfalke.httpd.app/test.html
- Interesting default rendering choice for `()` in their demo pretty printer. It renders a space before each opening parenthesis.
- Isn't what you describe a PID-controller: https://en.wikipedia.org/wiki/Proportional%E2%80%93integral%...
AFAIK that is the common approach to solve this problem, but it still needs some degree of sensor accuracy?
- SEEKING WORK | Part-Time | Remote | Europe
Senior Software Engineer specialized in Django, Pipeline-Development, GIS and applied machine learning in the context of earth observation, sensor mapping in general and remote sensing in particular.
e-mail: freelancer-hn@zetalabs.io
Stack:
Available 20 to 100 hours/month (@110e VHB).- Django - Python (with eco-system: numpy, pytorch, etc.) - Linux - Godot - GDAL - OpenStreetMap - Rust - Bash-VoodooExample work: https://turmfalke.httpd.app/test.html
Happy coding and nice to meet you!
- Interesting. Came to similar conclusions when analyzing my (httpd) access logs for https://turmfalke.httpd.app/demo.html ... but so far nothing really out of the ordinary.
- 3 points
- Yes, I am aware of Sentinel-2 10m data (RGBN), there are even commercial offerings. Actually the storage requirements are not that big for 10m, like ~4TB for the entire (non-water) world. Napkin math:
This results in 15000 * 10980^2 * 4 * 0.5 / 1024*4 ~ 3.3TB. This matches commercial offerings like in https://cloudless.eox.at/#data. Of course we have to add lower-scale imagery that is often used to provide XYZ tiling that would further increase the storage requirements.- 15000 Sentinel-2 scenes over land - 10980^2 pixels per scene - 50% lossless compression per scene - 4 channels (RGB and infrared)Thanks for the link to OpenTopography, it's an interesting project and elevation data is extremely valuable.
- It's a nice start but what we also need would be an "OpenRasterMap" project - a project where we collect raster data (more and more data gets available) and store the entire planet (RGBN aerial imagery) in let's say 1m/Pixel.
It might be feasible to store entire planet's raster tiles in 10 years in a (beefy) desktop machine.
- That's actually a nice idea. I guess we will see more software in the source code dependencies analysis space. There's so much code and often it's nice to have some kind of metrics (LOC, PageRank, ...) to get a grasp of what's important in a codebase.
- Wow never heard of GBIF, but you seem to offer useful data. Am I correct that you are in essence providing georeferenced animal/plant population data across the globe in mostly CC license?
So, good luck!
- Other HN discussion: https://www.hackerneue.com/item?id=30410077
- > I feel like if I am worried about those issues, when would I ever use sqlite instead of Postgres?
Sometimes you do not want to run an additional process/daemon like postgres. Your state is in essence now a file on some file system that you can atomically (full ACID) update using multi processing without the need for more complex machinery - you can get very far with this architecture.
- That would have never worked because such a license would be at odds with free and open source licensing and Docker wouldn't have gotten any traction in these communities (that provide the infra backbone of the whole stack).
I get your intention, but monetizing infrastructure and systems code is pretty hard.
- "Working" can be interpreted differently. 75% accuracy (?) is not that great for predicting a specific class (depending on distribution on course).
If you need high accuracy, let's say for e.g. estimating eco system performance based on specific plant distribution, 75% is very low (especially if you want to feed it into another predictor) compared to a professional field biologist.
- Probably because it is mostly compared to Python - which is arguably a low bar to beat.
- > GHC'ss linear types don't give you uniqueness types in the same way rust does
Why, though?
Is it because GHC's linear types are a superset of Rust's linear types? I guess that could rule out some features the compiler is able to prove (or not).
- Yeah and hosting it by yourself is slightly non-trivial as the storage requirements are in the PB range.
- That's a good one, did not know that. Interesting read.
showcasing my project over the last years (again). The updated LC-Product works now pretty streamlined and it makes pretty interesting (and surprisingly good to compress) maps.
Stack is a collection of adjustable U-Nets that make predictions that are merged together to derive the final map.
Happy to answer questions.
Happy holidays and happy hacking.