Join devRant
Do all the things like
++ or -- rants, post your own rants, comment on others' rants and build your customized dev avatar
Sign Up
Pipeless API
From the creators of devRant, Pipeless lets you power real-time personalized recommendations and activity feeds using a simple API
Learn More
-
Suggestion for dealing with ocean, build a terrain map using topographical data and key using that. Some free terrain datasets https://www.opentopodata.org/
-
Actually that's not a bad idea at all.
Api limitation would take ages on that site, but in theory, if I open the maps and align and scale them (so we get a roughly one to one correspondance between the pixels on each), then its striaghtforward to consume the one biome map, use the elevation map as a key, and then using PIL, copy and output only those source image pixels which would be above sea level.
This of course wont work for death valley, but that'll be easy enough to fill in by hand. Lot quicker than hand editing the full map too.
Thank you Atheist!
Cant believe I didnt consider this before. -
@atheist beats building a full parser/renderer for 17gbs worth of shapefiles.
-
In the mid-90s I had a job converting 75 degree paper maps to digital maps for the government. I had a digitizing table with a janky mouse-like device that had magnetic wire crosshairs that I’d have to align with whatever feature I was mapping. Usually roads and boundary lines. Just pointing and clicking to make dot-to-dot sets of arcs that would translate to coordinate points in an ESRI Arc-GIS Oracle database. Then I had to write and run scripts to clean up the data for storing in a digital warehouse. It was time-consuming and tedious work. In the end I mapped millions of acres.
-
@stackodev that sounds like the coolest fucking job. Thank you for your blood sweat and tears.
We've come a long way in some ways. -
@TurtleTheDev holy shit, that's so far north you-re probably a viking.
Maps really are cool.
I'll mail you one so you can navigate and sail the ol' long boat down to my neck of the woods. -
@Wisecrack Thanks. I deeply regret not doing a separate contract which was getting on a 4-wheeler and driving out into the national forest to take GPS points of various roads. What a cool experience that would’ve been. I often wonder whether I would’ve enjoyed a GIS career more than this web dev career I’ve had for 25 years. I could’ve even gotten into the remote sensing industry and maybe even done some stuff with satellites with LiDAR and such.
-
@stackodev Is it too late to dream different dreams, dreams you dreamed so long ago?
-
@Wisecrack It feels like it. I’m older and getting weary of building any kind of career. Planning on trying to retire early and get more meaning out of life than a constant grind 8:30-5:30 job in anything at all. Maybe I’ll finally try to finish writing one of the many manuscripts I started over the years and become a published author.
-
@stackodev Thats crazy. Even 3y's later your story about your career in mapping is one of my favorites on DR.
-
@Wisecrack I lived in a really cool time and in a stunningly beautiful area of the Southwestern U.S. There are nights when I can’t sleep that I relive that era and place in my mind and wish I could go back. So much about today is amazing but also so, so screwed up.
-
@stackodev and there are fewer places to be alone and isolated with each passing year.
Related Rants
Creepy AF!
My God is map development insane. I had no idea.
For starters did you know there are a hundred different satellite map providers?
Just kidding, it's more than that.
Second there appears to be tens of thousands of people whos *entire* job is either analyzing map data, or making maps.
Hell this must be some people's whole *existence*. I am humbled.
I just got done grabbing basic land cover data for a neoscav style game spanning the u.s., when I came across the MRLC land cover data set.
One file was 17GB in size.
Worked out to 1px = 30 meters in their data set. I just need it at a one mile resolution, so I need it in 54px chunks, which I'll have to average, or find medians on, or do some sort of reduction.
Ecoregions.appspot.com actually has a pretty good data set but that's still manual. I ran it through gale and theres actually imperceptible thin line borders that share a separate *shade* of their region colors with the region itself, so I ran it through a mosaic effect, to remove the vast bulk of extraneous border colors, but I'll still have to hand remove the oceans if I go with image sources.
It's not that I havent done things involved like that before, naturally I'm insane. It's just involved.
The reason for editing out the oceans is because the oceans contain a metric boatload of shades of blue.
If I'm converting pixels to tiles, I have to break it down to one color per tile.
With the oceans, the boundary between the ocean and shore (not to mention depth information on the continental shelf) ends up sharing colors when I do a palette reduction, so that's a no-go. Of course I could build the palette bu hand, from sampling the map, and then just measure the distance of each sampled rgb color to that of every color in the palette, to see what color it primarily belongs to, but as it stands ecoregions coloring of the regions has some of them *really close* in rgb value as it is.
Now what I also could do is write a script to parse the shape files, construct polygons in sdl or love2d, and save it to a surface with simplified colors, and output that to bmp.
It's perfectly doable, but technically I'm on savings and supposed to be calling companies right now to see if I can get hired instead of being a bum :P
rant
data
mapping