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Wrangling / analysis / plotting of MagnaProbe snow depth data.

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magnaprobe-tools

Tools to better wrangle / analyse / plot MagnaProbe snow depth data.

The MagnaProbe is an automated snow depth measuring device that records a geolocated snow depth at the click of a button. See Sturm & Holmgren (2018) for instrument details.

This repository is a set of 'first cut' tools designed for rapidly checking the quality and nature of your MagnaProbe data.

Wrangle messy data that looks like this:

TOA5 29037 CR800 29037 CR800.Std.27 CPU:Geophys2_GPSProbe.CR8 60528 OperatorView
TIMESTAMP RECORD Counter DepthCm BattVolts latitude_a latitude_b Longitude_a Longitude_b fix_quality nmbr_satellites HDOP altitudeB DepthVolts LatitudeDDDDD LongitudeDDDDD month dayofmonth hourofday minutes seconds microseconds
TS RN degrees minutes degrees minutes unitless
Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp Smp
2017-11-14 11:27:00.75 5721 100001 7.283 13.75 65 2.4724 -147 -25.0191 1 5 1.7 723.9 0.48 0.04120666 -0.416985 11 14 11 27 0 750000
2017-11-14 15:14:14.75 5722 100002 7.732 13.78 65 2.4724 -147 -25.0163 1 5 1.7 723.1 0.51 0.04120666 -0.4169383 11 14 15 14 14 750000
2017-11-14 15:14:15 5723 100003 4.138 13.75 65 2.4721 -147 -25.0147 1 9 0.9 729.4 0.28 0.04120166 -0.4169117 11 14 15 14 15 0

To a table like this:

timestamp counter Latitude Longitude Snow Depth m geometry
0 2017-11-14 15:24:38.5 100002 65.0403 -147.418 0.7892 POINT (480320.68 7213010.28)
1 2017-11-14 15:24:39 100003 65.0403 -147.418 0.7684 POINT (480320.76 7213010.46)
2 2017-11-14 15:24:39.5 100004 65.0403 -147.418 0.7735 POINT (480320.76 7213011.02)
3 2017-11-14 15:24:40.25 100005 65.0403 -147.418 0.728 POINT (480321.62 7213010.83)

So you can quickly plot these:

Geo24hist

Geo24map

Dependencies

  • geopandas 0.6.2
  • pandas 0.25.3
  • matplotlib 3.1.2
  • numpy 1.17.3

Warnings

The tools are intended to be flexible, but are configured largely for a "stock" MagnaProbe. Non-English language users or users with differently programmed hardware will need to tweak field names, calibration patterns, etc. Finally, this is not a 100% process. If you look closely, there may still be suspect points in the example data - but one of the reasons to rapidly generate the quick and dirty plots is to look for instrument errors or for data that should be discarded.

Usage Examples

python magnaprobe.py example_data/Geo2_4_raw.dat 32606 output_data/Geo2_4_UTM.shp output_data/Geo2_4_UTM.csv

python plot_magnaprobe.py output_data/Geo2_4_UTM.shp --save_plots true

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