grasslidarqgisrastersaga
How can I compute a raster showing the number of return points per square meter using SAGA GIS or other open source software?
My goal is to obtain a mask which would show me the places (cells) where there were no hits and would help me in interpreting LiDAR-derived data.
You either need to solve the system problem or perform a substitute or work-around comparison. Because you don't provide details about the error, I conclude you're looking for a work-around.
Consider converting both TINs to raster format, where a little map algebra does the rest. For example, the RMS measure of difference between the TINs is obtained by subtracting one grid from the other, squaring the result, and taking the square root of its average value. The answer depends on the cellsize (and grid origin) you use, but as the cellsize grows small, the answer will converge to the one you would obtain using the TINs directly.
There are many tools and libraries to perform such comparisons. They are the bread-and-butter operations of raster GIS packages like Spatial Analyst, IDRISI, and GRASS.
Note that no such procedure, whether applied to the TINs or some other representation, can estimate accuracy (which concerns agreement between the TIN and reality): it can only compare one data set to the other. Both could be hugely inaccurate, yet in close agreement.
There is nothing unusual about interpreting these results: one inspects both maps and the difference map, looks for outlying values in their differences, characterizes the statistical distribution of the differences, assesses the spatial correlation of the differences, identifies locations where clusters of high or low differences occur, etc., just as always.
I would suggest refFunctions plugin.
If your Telling layer is the grid, and Data layer is the points,
Open the attribute table of the Telling layer, and start Field calculator. Then create a new field with an expression intersecting_geom_sum( 'Data', 'E impact')/"hits".
(assuming "hits" is the field you have stored the number of hits).
Then Telling attribute table would be like below.
Best Answer
I develop a free and open-source GIS called Whitebox Geospatial Analysis Tools (can be downloaded here) that has extensive analysis functionality for processing LiDAR data. Whitebox contains a tool specifically for calculating the point-density of LiDAR LAS files called Point Density LiDAR.
The tool is highly specific to LiDAR, taking one or more LAS files as input. It can also calculate the density of first-return points only, last-return points only or all-returns. Additionally, if your LiDAR data contains classification information, you can optionally exclude points based on their classification type (e.g. buildings or vegetation points).
There is a second tool, called Hex-binning, which will also perform a density-type analysis on LAS files (Point-type ShapeFiles as well), but will output a vector (ShapeFile) hexagonal grid. This can be a very effective way of visualizing high-density point coverage (see blog on hex-binning here).