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So these photon measurements
 are from central Montana,

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an agricultural area that most people

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aren't always familiar with,
 and they think of Montana.

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But Montana grows a lot of grain,
 a lot of foodstuffs, wheat,

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lentils, peas, and these measurements

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are right in that kind
 of agricultural heartland of the state.

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Exactly dead center, 

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00:00:26,659 --> 00:00:28,461
geographic center. 

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So because we're working
 in an agricultural area

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that has a lot of different crop types,
 and so snow accumulates

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and persists at different rates
 depending on the crop type.

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And a lot of is because of wind. 

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And so what we're able to do using lidar is
  we're able to measure or quantify

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how that snow persists in different
 crop types and where it persists.

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00:00:49,749 --> 00:00:53,887
And and that's something that has not
 been done very much to really understand

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how crop type and stubble,
 height influence snow accumulation.

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00:00:58,992 --> 00:01:02,929
And so lidar allows us to do that
 and flying over it with with drones

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or UAVs really allows us
 to do a more focused study.

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Neumann: By comparing ICESat-2 measurements
 from times of year

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when there's no snow on the landscape
 with following passes,

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when there is snow on the landscape,
 allows us to measure the depth

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or the height of the snow
 sitting on the land.

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In this scene in Moccasin, Montana,
 this is an agricultural area

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where the snow cover can often
 be discontinuous and patchy.

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The small footprint size of ICESat-2,
 which is right around 10 meters

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or about 30 feet, and the fast pulse
 repetition rate of the laser

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allows scientists 

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to measure small scale changes
 in the snow depth across the landscape.

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That can be important
 in agricultural areas like

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Mocassin, Montana,
 where that seasonal snowfall

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is a primary source of the spring water
 to allow crops to start growing.

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Sproles: So another way that
 ICESat-2 is potentially valuable

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looking forward is to combine that data
 with with new techniques

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00:02:01,621 --> 00:02:03,623
that are coming off new sensors. 

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00:02:03,623 --> 00:02:07,360
For example, NASA is going to be launching
 NISAR next year.

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That will really allow us
 to compare and NISAR

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00:02:11,331 --> 00:02:13,032
satellite uses
 a different kind of sensor. 

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00:02:13,032 --> 00:02:17,070
It uses kind of a microwave-based approach,
 as compared to a laser based approach.

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00:02:17,504 --> 00:02:20,140
I think comparing those two
 with regards to snow

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depth, again, is going to provide
 a lot more detail and insights

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that will weigh at much more broad scales
 than we can do with this

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more focused study area.