[twelvechairs]

I wonder what the gain is in doing this compared to using government lidar data - it seems this is available for new brunswick [0]

The 0 cost solution would be to use this lidar data for topography, perhaps even for tree clusters, then use an aerial photo to help plot on some extras like roads. Maybe there's a little accuracy difference I'm not sure

[0] https://open.canada.ca/data/en/dataset/80ccc975-d6ec-9e24-a7...

[bendauphinee]

There's a lot of ground clutter for starters. A lot of what I've surveyed so far has been ground under dense deadfall (due to previous logging), and my resolution is better than the LIDAR, for those spots.

Also, the accuracy, I expect that since I can get precise measurements, my maps of the streams, marshy areas, and other features are going to be a lot more comprehensive. Basically, I can get detail down to the level I want, just for the time I want to spend putting stick to ground.

[fghorow]

I'd be quite eager to see the elevation comparison (residual) between LiDAR and your surveying.

In my game (geophysics) LiDAR is basically known for its ability to see through canopies -- through the virtual holes between leaves. They define the last arrival as "ground" level, and call it a day.

Now, I agree that deadfall (i.e. tree bits-and-pieces on the ground) has an ambiguity such that the tops of the deadfall would be reported as "ground" in the LiDAR definition. So, I expect that any residual map you might be able to create would -- in essence -- show the deadfall "topography".

Very nice project!!!

[bendauphinee]

I had not tried pulling the LIDAR, but yes, especially where the deadfall is 3-8 feet thick in the logged areas, I can already see spots where their generated topo doesn’t match my work.

[Qqqwxs]

If you want to go further down the LIDAR path, you might be able to improve the public data by making manual improvements to the point cloud classification.

For that sort of terrain it's common for classification algorithms to put vegetation (e.g. deadfall, small bushes) into the "ground" class, so when the terrain model gets triangulated using all the "ground" points there is erroneous bumps. If this is the case, you could reprocess the point cloud yourself and tweak the settings being used or make manual adjustments.

I'm not sure of the quality of the linked dataset, so maybe it would be difficult to find improvements. But you knowledge of on-the-ground conditions (and smallish scale of the area) means it's definitely possible.

Also, just in case you haven't stumbled across it, a "Digital Surface Model" (DSM) is different than a "Digital Terrain Model" (DTM)!

(surveying student here, very much enjoyed the writeup!)

[bendauphinee]

I had not come across the DSM term yet, thank you! I'll have to pull that thread once the snow makes this work completely impossible for the season :D

[twelvechairs]

Good points! It would be very interesting to see the comparison