First cuts of data

So today I was dragging the Riegl from level to level up the tall tower in the control plot. 18 levels, the heat, and it's pretty heavy. I was pretty much sopping after about 2 hours of it, and by the end, practically on my knees. Whose stupid idea was that? Oh.

Meanwhile, Andy's been furiously registering, slicing, dicing and generally working like a demon to pull out stem maps from the data so we can try and match them off the field data before we leave on weds night. He's produced a hugely downsampled pointcloud just to make life manageable until we can get our big machines in the lab on it. The examples below are from roughly 15 million points, which is < 1% of the data, and only from the upright scans. When we include the tilt scans, we'll obviously sample preferentially in the upper part of the canopy, and double the number of points.

An overview of the drought plot, coloured by height.

A zoom in of the largest tree in the plot - towards the centre back above.

 Amazingly, even in this (relatively) extremely sparse point cloud, the tops of some of the largest canopy trees are clearly visible. Also, the registration looks better than we could have hoped for. We've really been able to put what we've learned over the last 12 months into practice here, and I think it's really paid off. I may have even indulged in a very dignified whoop of delight on seeing this, slightly frightening Andy in the process.

A slice through the drought plot from 1.3 to 2.3 m above the ground. Lines running right to left are the wooden railings and runnels carrying the panels that keep the rainfall off the plot.

The slice through the data also shows up the wooden runnels that carry the panels very clearly. It's amazing to see them all laid out like this in such detail (the images above are rather low quality just because of the bandwidth) - and the trenches around the edges, clear of any vegetation. Even Lucy and Alex, who are extremely familiar with the plot, and essentially know every tree in there, are seeing it in a new way. It's funny - you can get buried in the details of measurements and kit, and data and logistics, but when you see the results stand out so clearly, it really brings home why we do these things.