Snow depth paper published
Our peer-reviewed paper on mapping snow depths was recently published in the journal “The Cryosphere”. To my knowledge, there is no better way to measure the depth of snow on watershed-scales than we have demonstrated there using fodar. Understanding snow depth is enormously important to many aspects of society, not the least of which are that most people’s drinking water ultimately comes from snow melt and that global climate is in part driven by the amount of the earth’s surface covered by snow.
The basic idea behind the method was simply to subtract a snow-free elevation map from a snow-covered one, with the difference being snow depth. The idea behind this has been around for a long time and has been applied often to bigger changes in topography such as on glaciers, but until now no one could afford to make maps of sufficient resolution to do this with snow (I was unable to find a single study where some one actually tried this with digital photogrammetry from a frame sensor). Of course the quality of the snow depth measurement depends on the quality of the maps being subtracted. So we spent a lot of time in the paper demonstrating the quality of these maps, with the ultimate test of comparing our snow depth maps to over 6000 hand probed measurements of snow depth and finding they were essentially identical.
While the accurate measurement of snow depth from an airplane is a big deal, perhaps an even bigger deal is that because snow is among the most difficult surfaces to photograph well, our results suggest that any change in height to the earth’s surface of more than a few centimeters can be measured affordably now. The implication here is potentially huge to earth science. Until now, nearly all of our field plans have been wrapped around trying to make point or line measurements in areas we think are going to have changes representative of the larger area of interest, and then extrapolating those measurements to that larger area. But extrapolation is a method of desperation — we only do this because we cant afford to measure everything. Now it is within our grasp to skip that whole extrapolation step and make direct measurements over our entire areas of interest. Of course Fairbanks Fodar has been doing this for a long time already, but now we have a paper within the peer-reviewed literature documenting this. And if it’s published on the internet, it must be true, right?
You can find a copy of the paper in the viewer below, but if that doesnt work follow this link.