Poor workflow?

[Schyler Brown]

Hey everyone,

This is a long one, forgive me...

I am hoping to see if my workflow looks solid to anyone with experience in plot level analysis.

The problem is as follows: I extract height metrics at plot level (see workflow below), combine height metrics into csv containing plot level dependent variable (Basal Area), run my regression in R using independent variables suggested by prior research with good data, but I get an r^2 of about .24... 

My suspicion is that something I am doing during my data processing is wrong and was hoping someone who has done this could look it over. The reason for my suspicion is that 1) I am new to lidar and data processing and 2) my canopy cover data looks pretty messy...

WORK FLOW:

Unlicensed LAStools (I'm a grad student)

      1) index, tile and buffer (lasindex, lastile, 200m tiles, 20m buffers)

       2) ground classify (lasground, small buildings so select towns, ultrafine)

       3) replace z (lasheight)

       4) remove noise (the default settings worked well, I didn't have much noise to begin)

       5) clip 1/10acre (.04ha) plots

       6) extract cloud metrics (tried both FUSION and LASCanopy)

       7) BA is positively skewed, take natural log (RStudio:   datum$logBA=log(datum$BA)

       8) run regression in RStudio (results=lm(BA~Cov+P99, data=datum)

       9) results: r^2=0.24

Now, I've checked a raw clipped plot against the normalized one, and it looked fine, no loss of data or anything, so I'm pretty confused... I'll paste a link to some samples.. maybe 1/10acre .04ha plots are too small? point density is too small?  Thanks.

https://drive.google.com/drive/folders/1B1R5KvH-4L4lFNxNifeQRiaFoY9r_Sm3?usp=sharing

[Schyler Brown]

Update:

I have run my statistical methods by my professor, and they approved. I also tried using Volume as a dependent variable instead of Basal area, and got much better results. Seeing how a regression for basal area and lidar probably relies more heavily on canopy cover than volume, I suspect that it is in fact my canopy cover lidar data that is at fault. 

So now the question becomes, why? I've checked canopy cover before and after each step of my workflow, and it appears to look the same... 

Thanks all!

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