LiDAR scans are finding hidden Roman roads and cutting crime
wired.co.uk
wired.co.uk
And despite the significance of the discovery, there is almost no funding for continued research, and making basic discoveries of where artifacts might be located is still a major bottleneck.
Uses UK LIDAR data to show shadow maps. This can be used to show urban areas which are permanently in shadow. Or just as a cool way to map the country.
http://chris-osm.blogspot.com/2015/09/extracting-building-he...
The creator uploaded the convert-to-3D program, so once you've found the files it should be possible to turn them into 3D files provide you're comfortable running stuff from the command line and following his advice on parameters. https://github.com/andrewgodwin/lidartile
I haven't tried it yet though - it's on the to do list!
I started doing something similar when the Welsh LiDAR data was released ( details in https://theretiredengineer.wordpress.com/category/lidar/ ). I had written some code to manipulate PLY files when I was trying to create 3D models of standing stones using photogrammetry. It was then fairly easy to modify that code to create PLY models using the LiDAR data. However I found two problems for the area that I was interested in ( parts of south west Wales )
1. The LiDAR data coverage was a bit patchy
2. There were gaps in the data files which resulted in holes in the model
There was nothing I could do about #1 but it should be fairly easy to fix #2. The other option would be to use a GIS of some sort to process the data.- http://potree.org/potree/examples/ca13.html
- http://potree.org/potree/examples/showcase/lake_tahoe.html
I've been using LIDAR data for doing canopy height modeling, and screening remote areas for possible exceptional/champion trees prior to checking it out in person.
Haven't put anything online yet because I'm very new to GIS and this sort of thing, and am still getting over the horror of what it takes to build a functioning workspace and data pipeline.
("Just take this TIFF and convert it to a CSV" is a phrase I never thought would make sense, but here it does.)
PDAL is my current software crush.
Getting it running under Wine was dead-simple. There's a significant community around it, and the author fights for open formats.
Checking out PDAL is on my todo list for sure.
For the UK, it's the Ordnance Survey (https://www.ordnancesurvey.co.uk)
http://www.nationalarchives.gov.uk/doc/open-government-licen...
Seattle / King County just finished a rescan in 2016/2017 and the data is stunningly good. [2] Really good consistency and density. The DLM/classification/cleanup seems excellent.
[1] http://pugetsoundlidar.ess.washington.edu/
[2] (private, need an account) http://pugetsoundlidar.ess.washington.edu/lidardata/restrict...
Really though - as a beginner, I started with the 2003 data, and had a really hard time with it. Had to deal with file conversions rerun ground classifications and thin and do all sorts of cleanup to sorta get where I was trying to go.
I personally [1] have imported it into Unity for a terrain heightmap.
[proceeds to use dragnet to crack down on people dumping stuff in the woods]
Illegal dumping is scum of the earth stuff.
(murder is the extreme example, but that's the argument you've just made, that devoting resources to prosecuting some particular crime is a slippery slope to abusing the homeless)
Even if it’s not a seriously dangerous substance, making the landscape ugly like that is still a really shitty thing to do to your fellow citizens. I think it would be great if more dumping violations could be prosecuted.
A lot of the country isn't covered, and what is there is pretty dated, but there's a recent capture of the entire west coast available.
USGS's 3DEEP data for the National Map covers lots of federal and private land. Open Topography holds lots of research data funded by various federal organizations (NSF, NOAA, others) amongst other stuff. State-level Departments of Natural Resources very commonly host survey data.
Some time ago it was mentioned that SDCs can't use deep-learning because it is not sufficiently reliable, and that instead techniques like LiDAR should be used to recognize objects.
However, this made me wonder: how does the car recognize road-signs and traffic lights?
Or is DL classification at 100% accuracy?
(I'm mostly joking, but the answer does seem to involve big databases of what the signs and roads are expected to be. I'm not convinced that most of the current "self-driving" solutions can cope with roadworks, traffic cones, diversions etc)
Short answer: Self driving vehicles do use deep learning, but they avoid some types not because it is unreliable, but it is processing power intense. Traffic lights, road signs, pedestrians etc.. That's a whole ball of wax to unravel. Check the lecture, its fantastic imo.
https://arxiv.org/abs/1707.08945
TLDR: the authors demonstrate that it's possible to apply minor perturbations to signs (for instance, rectangular stickers) that don't significantly change the appearance to humans but cause a classifier to confuse a stop sign with a speed-limit sign.
eg, a typical high-quality survey will involve:
- Something like a Leica ALS80 [1]
- A Cessna + good Pilot, the plane needs to be really well instrumented.
- A team of surveyors on the ground to establish ground controls, and occupy points for GPS RTK calculations
- A bunch of post-processing to normalize the data, remove birdies and pits, do ground classifications, etc. (The raw data from the sensor before the processed point cloud is built is really really raw.)
A much cheaper approach which seems to be catching on is UAV photogrammetry. It's processing intensive, but no special sensors are required, and in the end you still get a pointcloud. Sensefly is a company that makes these types of UAVs.
[1] https://leica-geosystems.com/en-us/products/airborne-systems...
[1] https://www.theregister.co.uk/Design/page/reg-standards-conv...
Or as one incarnation of Joker put it, "why so serious?".
Sure, maybe the local, community field you and me play on, but not the ones where "real" matches are played. They have a standard size.
FIFA for example have the dimensions in their first law: http://www.fifa.com/mm/Document/FootballDevelopment/Refereei...
Probably they mean a standard football field.