Searching for Stations

Where in the world are these stations?

One common frustration is finding relevant stations for analysis and validation

What are some methods you have used to identify stations that fit your research?

# Imports
from datetime import datetime
import pandas as pd
import geopandas as gpd
from pathlib import Path

from metloom.pointdata import SnotelPointData, CDECPointData, MesowestPointData

try:
    import folium
except Exception as e:
    !pip install folium

try:
    import mapclassify
except Exception as e:
    !pip install mapclassify

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Search for points in an area

# Find your area
sf_path = Path("./data/outline.shp").expanduser()
sf = gpd.read_file(str(sf_path))
sf["name"] = ["Our outline"]
variables = [SnotelPointData.ALLOWED_VARIABLES.SNOWDEPTH]

# What does the area look like
sf.explore()

Make this Notebook Trusted to load map: File -> Trust Notebook

# Find all the points in the area for our variables
points = SnotelPointData.points_from_geometry(sf, variables)
print(len(points))
# This is an iterator
print(type(points))
# It contains the points in a `points` attribute
print(points.points)

2
<class 'metloom.pointdata.base.PointDataCollection'>
[SnotelPointData('637:ID:SNTL', 'Mores Creek Summit'), SnotelPointData('978:ID:SNTL', 'Bogus Basin')]

What if I want a station nearby?

# buffer - add buffer (in degrees) to extents
print(SnotelPointData.points_from_geometry(sf, variables, buffer=0.5).points)

# within_geometry - doesn't do anything since our geometry is already a square
print(SnotelPointData.points_from_geometry(sf, variables, within_geometry=False).points)

[SnotelPointData('978:ID:SNTL', 'Bogus Basin'), SnotelPointData('637:ID:SNTL', 'Mores Creek Summit')]
[SnotelPointData('637:ID:SNTL', 'Mores Creek Summit'), SnotelPointData('978:ID:SNTL', 'Bogus Basin')]

# imports for a static map
try:
    import contextily as ctx
except Exception:
    !pip install contextily
    import contextily as ctx
import matplotlib.pyplot as plt
from shapely.geometry import Point

# Make a static plot of the points

# turn that iterator into a dataframe
df = points.to_dataframe()
# look at what is in the dataframe
df.head(10)

def remove_z(geom):
    if geom.is_empty:
        return geom
    else:
        return Point(geom.x, geom.y)

df.geometry = df.geometry.apply(remove_z)
df = df.set_crs("EPSG:4326")


print(df)
ax = sf.to_crs("EPSG:4326").plot(alpha=0.1)
ax = df.plot(ax=ax, color="red")
ctx.add_basemap(
    ax,
    # source=ctx.providers.OpenStreetMap.Mapnik,
    source=ctx.providers.USGS.USTopo,
    crs=df.crs,
    # zoom=5
)

                 name           id datasource                     geometry
0  Mores Creek Summit  637:ID:SNTL       NRCS    POINT (-115.66588 43.932)
1         Bogus Basin  978:ID:SNTL       NRCS  POINT (-116.09685 43.76377)

Our plot could be more interesting

# plot the shapefile
m = sf.explore(
    tooltip=False, color="grey", highlight=False, style_kwds={"opacity": 0.2}, popup=["name"]
)
# plot the points on top of the shapefile
df.explore(m=m, tooltip=["name", "id"], color="red", marker_kwds={"radius":4})

Make this Notebook Trusted to load map: File -> Trust Notebook

Extra

How would we get the daily data for the first point from points?