Strelok ID: 2f7e6a March 1, 2019, 12:34 p.m. No.652818   🗄️.is 🔗kun   >>2855 >>3105

>>652782

Following on this, I encourage every strelok to look into learning the basics of GIS and acquiring a dataset of their local area. An extremely robust map can be created using <50GB, provided your local government or university has the data available. Pic related: a basic map I've been cobbling together of the tidewater region as an experiment. You can see that different cities have different data, so it's somewhat inconsistent, but it commonly includes things like military bases, emergency services, roads, addresses, building footprints, and census data (shown here to denote the percentage of blacks in a neighborhood.)

I can say that lots of people in military intelligence have massive hardons for GIS, and while a lot of that is from elderly officers falling for ESRI marketing, it's definitely a step up from doing things on Google Earth or paper maps.

Strelok ID: 2f7e6a March 1, 2019, 5:42 p.m. No.652867   🗄️.is 🔗kun   >>3592

>>652855

>Seams neat, how big do those things get though?

Depends on what you want. QGIS is pretty robust in how you can manipulate data. I filtered the roads to only include Interstates and US Highways in pic related and then simplified the polygons on the county boundaries and got the whole thing down to 50MB.

>Paper maps could do most of the work, only really need to know the locations of what you are looking for (say police stations for example), then something thats text based only should take up <5GB

QGIS supports importing external basemaps, which gives you all the baseline info available in such maps in addition to any additional information you get from either government databases or personally accumulated data. Second pic related is OpenStreetMap with an overlay showing exactly which roads don't have stoplights, and neighborhoods with a black population more than one standard-deviation above average for the area, which is very important if you remember footage from the chimpouts in 2014-2016. The data involved in this map is under 2MB (not counting the base map.) It took me exactly 62 minutes to learn how to do all this, do it, and write this post.