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An idea is: Use the lidar data to classify ground and non-ground points. Then, build a Digital Elevation Model (DEM) from the ground points. Here is a way of doing it. Use the RGB values from the aerial images to color code the lidar point cloud. Here are examples showing how this can be done. Now, it is possible to display the DEM and the color-coded ...


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I know this is an old question but I was stuck too (I have to model a 3d globe that uses a TMS) and found the "altitude" of the camera partly thanks to Igor Brejc's reply and mostly thanks to this article: http://wiki.openstreetmap.org/wiki/Zoom_levels there is a mistake in their formula btw ; the +8 in S=C*cos(y)/2^(z+8) should not be there. in my case ...


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In R, use hist3d from the rgl package. demo(hist3d) will show you a very low resolution example, commented on here: http://www2.warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/3d_bar_chart


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Actually, you don't need to add a z-dimension in order to achieve the building-height that they use in that blog post. In fact, the map pluto image you posted is using the same cartocss method. Basically, you just need a column in your dataset that includes some variable for building-height. In their case, they have three columns, z_small, z_large, and ...


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Thank you for clarifying your question as it was previously quite unclear. You can read a multiband raster using the stack or brick function in the raster package and assign the associated RGB values to an sp SpatialPointsDataFrame object using extract, also from raster. Coercion of the data.frame object (which results from read.csv) to an sp point ...


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An alternative to render LiDAR data and RGB values in 3D is FugroViewer. Below, there is an example with sample data they provide. I used the file entitled Bmore_XYZIRGB.xyz which looks like this: When opening in Fugro Viewer select the corresponding fields available within the file (in this case, a .xyz file): Then, color the points using the RGB ...



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