I am tempted to import this data into my system and build a pivot table of building type (PRIM_OCC) by state.
I could then graph the data (pie chart, bar graph, etc) to show how the building type distribution (e.g. residential ratio per hospital) varies between the states.
One of the uses for something like this is to combine it with the best freely-available elevation data (processed/gap-filled SRTM mission + ASTER DEM data) for terrain height, and then landcover data for trees and foliage, in an attempt to predict 3GPP rev-whatever (4G/5G) radio coverage from tower, monopole and rooftop cellular sites.
People have been post-processing and working on the SRTM1/3 data set for the US48 states for something like the last twenty years, and in some cases combining it with more recent space radar data.
VHF/UHF repeater propagation maps and similar are another application. For both ham radio and public safety system more 'serious' radio purposes.
Or to combine with other data sets for things like population per zip code or data sets on demographic info per zip code relative to the density of buildings, unique structures.
Last mile facilities based ISPs and electrical grid operators and similar can use per-structure data sets like this to do calculations on network build or overbuild/ugprade/augmentation costs for specific geographic areas.
The precision with which Israel have exacted what appear to be controlled demolition of structures strongly suggests to me that targeting teams have fairly accurate ideas of building structure and critical weak points, to the point that they know specifically where, and how many times, to hit a structure to collapse it.
An application that simulates shadows at a particular location. For real estate purposes, seeing what kind of sunshine you would get in your backyard when you purchase that house with a backyard in the north.
The geometry is just the building footprint. You could probably do some sort of estimate as to how likely the yard was to have sun, but it wouldn't enable doing anything detailed.
CoreLogic was doing something like this, but line of sight from a window and then be able to possibly identify the scene / view that can be had from that window.
There's a company that does HVAC proposals for technicians who want to generate sales. Knowing residential buildings footprint and layout can be helpful to estimate job size.
I am tempted to import this data into my system and build a pivot table of building type (PRIM_OCC) by state.
I could then graph the data (pie chart, bar graph, etc) to show how the building type distribution (e.g. residential ratio per hospital) varies between the states.
https://data.hrsa.gov/tools/shortage-area/mua-find
Interesting, but not what I was thinking.
https://m.youtube.com/watch?v=2ScBd-71OLQ
any cool ideas I could build with this data?
One of the uses for something like this is to combine it with the best freely-available elevation data (processed/gap-filled SRTM mission + ASTER DEM data) for terrain height, and then landcover data for trees and foliage, in an attempt to predict 3GPP rev-whatever (4G/5G) radio coverage from tower, monopole and rooftop cellular sites.
People have been post-processing and working on the SRTM1/3 data set for the US48 states for something like the last twenty years, and in some cases combining it with more recent space radar data.
VHF/UHF repeater propagation maps and similar are another application. For both ham radio and public safety system more 'serious' radio purposes.
Or to combine with other data sets for things like population per zip code or data sets on demographic info per zip code relative to the density of buildings, unique structures.
Last mile facilities based ISPs and electrical grid operators and similar can use per-structure data sets like this to do calculations on network build or overbuild/ugprade/augmentation costs for specific geographic areas.
An IDF counterinsurgency bombing campaign.
The precision with which Israel have exacted what appear to be controlled demolition of structures strongly suggests to me that targeting teams have fairly accurate ideas of building structure and critical weak points, to the point that they know specifically where, and how many times, to hit a structure to collapse it.
Three-strike hit: <https://yewtu.be/watch?v=ZFTK9V_mEjI>
Single-strike hit: <https://yewtu.be/watch?v=uHMjQnQTGvI>
Accurate mapping + structure data plus precision munitions is what makes such strikes possible.
Cartography was long considered national-security-level critical data, a situation only mooted by satellite surveillance beginning in the 1960s.
This was exactly what I thought. Not sure why you're being downvoted. Granted it's not very useful if you're just an average citizen.
Establish yourself in non-mapped structures is actionable.
Knowing when you're in a mapped structure is actionable.
An application that simulates shadows at a particular location. For real estate purposes, seeing what kind of sunshine you would get in your backyard when you purchase that house with a backyard in the north.
Something like this: https://shademap.app/
The geometry is just the building footprint. You could probably do some sort of estimate as to how likely the yard was to have sun, but it wouldn't enable doing anything detailed.
CoreLogic was doing something like this, but line of sight from a window and then be able to possibly identify the scene / view that can be had from that window.
There's a company that does HVAC proposals for technicians who want to generate sales. Knowing residential buildings footprint and layout can be helpful to estimate job size.
A sandbox game with a map 1 to 1 with the ground truth.
What would the licensing be? I have a test earth I'm doing this with in Godot, but am paranoid about using anything not GPL/CC compat...
i have no idea what that even means.
Something like: https://screenrant.com/infection-free-zone-steam-openstreetm...
Think along the lines of how MS Flight Sim used photogrammetry to let people fly over their houses
Project Zomboid on steroids
Note that there's a companion address database by the DoT:
https://www.transportation.gov/gis/national-address-database
Is that where the addresses came from?
Anyone know if this is commercial buildings only or does it include residential too?
Virtually all of the buildings are residential. There are 20x more residential than anything else.
Does it include bike sheds? I feel I could spend a long time on that part of the database.
:-)
Some may need an assist: https://en.wiktionary.org/wiki/bikeshedding
I had heard about bike shedding, and I still missed it too. I guess it was too subtle.
One of the criteria for inclusions is an area greater than 450 square feet.
You can look at it in a slippy map: https://gis-fema.hub.arcgis.com/pages/usa-structures (a couple clicks required from there).
In my area it doesn't particularly identify garages well, so you probably can't spend that much time on bike sheds.
Only if they're blue though. A true bike shed has to be some shade of blue.
Wonderfully executed joke. 10pts.
You only get + or -.
I love to see a wry comment being taken seriously too and this one did not disappoint.
I didn't take it seriously, I was looking for a spot to drop a link to the map and it worked fine.
Do you think my last sentence was earnest or something?
A lot of them don't have addresses. I wonder if it can be intersected with another data set that has more complete address list.
Desktop computers are amazing these days.
That computer is a monster! I wonder how many kWh this study cost.
this asm
[flagged]
[flagged]
Echoes of that sewing page with unclosed h3 tags...
https://web.archive.org/web/20140310190221/http://www.sewing...
Same thing happens to me with Firefox on iOS.