# Generating a DEM and DSM from correct LiDAR point classification

I am trying to generate accurate DEM and DSM for further analysis. I created a LAS dataset with a projected CRS of NAD_1983_UTM_Zone_19N in meters and the z CRS in meters as well. My question is on which classifications do I choose for the DEM and DSM. Here is the filter options I have in my dataset:

According to unh LiDAR data report class 2 is ground.

What I have done so far:

DEM I chose the class 2 points and used the las dataset to raster.

DSM In the predefined settings I chose first return and used the las dataset to raster tool.

Is this an accurate way of generating these two rasters? Do I not have to take into account the the unassigned class 1, noise class 7, reserved 11, reserved 17, reserved 18?

Additionally (I can ask this as a separate question if it gets requested to), when using the las dataset to raster tool the sampling value is defaulted to 10. I would like to change it to 2 or 3 (would be meters) to match the LiDAR resolution. I also plan on using the generated DEM and DSM for a least cost path analysis and I want them to be higher resolution. Will making the sampling_value 2 or 3 throw off the results or should I leave it at 10?

It appears that the nominal post spacing is 1m, so applying a sampling_value, where the sampling_type = "CELLSIZE", of 2 or 3 is acceptable