Show HN: High-resolution surface analysis with Lidar data(github.com)
github.com
Show HN: High-resolution surface analysis with Lidar data
https://github.com/r-follador/delta-relief
10 comments
I think the examples should make it more clear. Thanks to the high resolution of the data, you can see subtle changes in the slope (aka relief aka microtopography) that could hint to underlying remains of human settlements (usually some suspicious geometric patterns that you would not expect in a natural terrain).
See also here for an in-depth discussion on the potential use of such data: https://www.mdpi.com/2072-4292/15/6/1569
How do you suggest to change the description to make it less confusing?
See also here for an in-depth discussion on the potential use of such data: https://www.mdpi.com/2072-4292/15/6/1569
How do you suggest to change the description to make it less confusing?
Here's another article about the use of such data in South America: https://www.nationalgeographic.com/history/article/maya-lase...
Of course, nothing so exciting to be discovered in Switzerland anymore ;)
Of course, nothing so exciting to be discovered in Switzerland anymore ;)
> LiDAR has some interesting use cases in archaeology (Caspari, 2023), particularly for uncovering man-made structures that are hidden beneath vegetation or subtle terrain changes. It allows archaeologists to identify features such as ancient roads, walls, building foundations, and agricultural terraces that may be invisible to the naked eye or conventional aerial photography.
Wasn't this also how the cities in the Amazon were discovered as well? These maps are fascinating. I can see ancient structures everywhere! Then again I'm not a trained archeologist.
Wasn't this also how the cities in the Amazon were discovered as well? These maps are fascinating. I can see ancient structures everywhere! Then again I'm not a trained archeologist.
"Buildings and vegetation are removed, revealing the underlying topography."
I understand how vegetation could be removed, but buildings? How is that accomplished?
I understand how vegetation could be removed, but buildings? How is that accomplished?
A raw point cloud is run through a series of processing steps to label each point with a class, e.g. "Ground", "Low/Medium/High Vegetation", "Building", "Transmission Tower", etc.
https://desktop.arcgis.com/en/arcmap/latest/manage-data/las-...
There will be a different algorithm for each feature class. For example, points that are part of a building might be identified by finding groups of points that form a very flat surface. ML models can also do this based on training data.
https://pro.arcgis.com/en/pro-app/latest/tool-reference/3d-a...
The final digital elevation model (DEM) is then just taking the "Ground" class from the classified point cloud and using them to triangulate a surface. This differs from a digital surface model (DSM), which will triangulate a surface based on ground+building+vegetation points.
https://desktop.arcgis.com/en/arcmap/latest/manage-data/las-...
There will be a different algorithm for each feature class. For example, points that are part of a building might be identified by finding groups of points that form a very flat surface. ML models can also do this based on training data.
https://pro.arcgis.com/en/pro-app/latest/tool-reference/3d-a...
The final digital elevation model (DEM) is then just taking the "Ground" class from the classified point cloud and using them to triangulate a surface. This differs from a digital surface model (DSM), which will triangulate a surface based on ground+building+vegetation points.
Removing vegetation seems like a harder problem than buildings. Buildings generally have cuboids and other standard shapes, but how do you determine the difference between small trees, big trees, bracken etc?
It the Scotland we have heather that can coat hills but I’m not sure that you’d be able to tell the difference between that and a forest canopy to assume a height and then subtract. Maybe there’s more than the point cloud to work with.
It the Scotland we have heather that can coat hills but I’m not sure that you’d be able to tell the difference between that and a forest canopy to assume a height and then subtract. Maybe there’s more than the point cloud to work with.
Aerial survey LiDAR can process multiple returns from a single laser pulse. So, some energy might be reflected back from a leaf, but some energy will pass through (or around) the leaf, hit the ground, then reflect back to the sensor. Some systems can record 5+ points from a single laser pulse.
With this information, you can filter the point cloud to only include points from the final return, which is likely to be the ground/a solid surface unless the vegetation is very dense.
With this information, you can filter the point cloud to only include points from the final return, which is likely to be the ground/a solid surface unless the vegetation is very dense.
You don't even need multireturn, typically your point cloud will have points from the tree or whatever plus some that returned from the structure behind it.
SwissTopo has a separate dataset of buildings and structures in Switzerland, so they basically just subtract it from the LiDAR data.
The description confused me, as it describes the use of a real Lidar measurements to detect "change" in the terrain. But certainly, it can't be a temporal change before and after... to detect medieval settings in the data. Is the area still changing differentlybetween scans over multi year's? I don't think so.
I think this is visualization code highlighting natural VS. human train structures, at known locations of old settlements? Showing different approaches on how to visualize the man-made heights in the terrain.
But still, I'm lost how this could help finding new ones..