That’s excellent. I hope I can have an endeavor like that when I retire. You might peruse Carlson’s site to get an idea of what they do. They started purely in Survey, but now do everything from Ag, GIS and Construction to Crime Scene Forensics. They have a great library of videos and a YouTube channel. Might give you a few new looks at workflow. Have a great rest of your holiday weekend!
Yes, looking at the contemplative implementations of others is a great way to get ideas. I will check out their website.
Here is my first stab at a conformal, 3D elevation map where the elevation is relative to local ground. This shows the tallest trees are downhill from the flat top area. I had no idea. Drones & DD are wonderful. Once I import LiDAR data, I can improve its accuracy. Forest guys using Carlson Civil must do this all the time. And with a little work, it fits in my budget.
I re-did the z-to-color mapping, toning down the too-bright colors and tweaking the colors to have more equal perceptual steps.
Here is the conventional 3D elevation map of about the same region (just a little shorter on the right):
Amazing! So on the conforming map at the top left region, is the darker cyan/blue area 0 or evidence of an area that has gotten lower over time?
No, it just shows I’m lazy and did only 1D terrain adjustment in the X-direction (long direction). Now that I can see a real benefit (finding the tallest trees), I will put more effort into doing a 2D adjustment. Once I get the LiDAR data for this site, I can make a surface from it and then use Rhino to find the Z on this surface for each mesh vertex. Then I color the vertex using Zvertex-Zlidar.
10-4, very handy nonetheless. I could see using something similar for flight to flight dirt progress (excavation/Embank) maps. Or at least that is one of the things I am doing with the point cloud. I then import that back in and overlay in DD. Here’s an example map. It is a 3-stage progress comparison because there are separate operations for pond excavation, lot fills and road construction. I hope you can see the overlay layers. There is also a layer with transparency which allows you to darken the map so the overlays are a little more apparent. Remember that the last layer turned on is at the top.
For example. If you only have the CF Pond layer on this is what you see. All calculations are done between the flight data and the proposed design surface. This shows the delta map, scale for the colors and a volume report. Might be easier to read the report on the site.
That’s a nice example of mapping elevation differences.
I am also putting a color code bar next to my elevation maps (I cut them off for the screen shots in order to maximize the map size). In this case, the color bar seems to show purple between green-blue and dark blue, another interesting choice. A lot of the dark-blue region is wasted, with too little perceptual difference between the steps. Not quite as bad on the red side. Looks like about 30-stepped colors. It might look better if there were more green-blue colors and fewer dark blues. Similar on the red side, with more orange-red colors. Good to see the green and yellow are not over saturated; their luminosity has to be backed down to be more in line with the other colors.
The lime-green effect with the overlay reminds me of the wonderful green color on Bianchi bicycles.
Hi all! Just checking in to keep this discussion going.