Plot the SAIL and SPLASH Locations
Contents
Plot the SAIL and SPLASH Locations¶
In this notebook, we take a look at the domain for the Surface Atmosphere Integrated (SAIL) and Study of Precipitation, the Lower Atmosphere and Surface for Hydrometeorology (SPLASH) observation sites!
Imports¶
import geopandas as gpd
import fiona
import hvplot.pandas
import holoviews as hv
fiona.drvsupport.supported_drivers['libkml'] = 'rw' # enable KML support which is disabled by default
fiona.drvsupport.supported_drivers['LIBKML'] = 'rw' # enable KML support which is disabled by default
hv.extension('bokeh')
Read in the Data¶
The datasets we are using include:
The East River Watershed, which is located near Crested Butte, Colorado
-
If you are interested in looking at recent plots, check out their website
Surface Atmosphere Integrated Field Laboratory Instruments
Various instrumention focused on precipitation, radiation, etc.
east_river = gpd.read_file('../../data/site-locations/East_River.kml')
splash_locations = gpd.read_file('../../data/site-locations/SPLASH_Instruments.kml')
arm_doe_locations = gpd.read_file('../../data/site-locations/doe-arm-assets.kml')[:2]
amf_sensor_locations = gpd.read_file('../../data/site-locations/SAIL_Instruments.kml')
Add Latitudes/Longitudes to the Dataframes¶
The data come in as Point
data, but we want to extract the latitudes/longitudes from this - we can do this by calling:
.geometry.x
for longitude.geometry.y
for latitude
We do this for both the SPLASH/SAIL locations.
splash_locations['Longitude'] = splash_locations.geometry.x
splash_locations['Latitude'] = splash_locations.geometry.y
arm_doe_locations['Longitude'] = arm_doe_locations.geometry.x
arm_doe_locations['Latitude'] = arm_doe_locations.geometry.y
Visualize our Data¶
We use both static/dynamic methods of visualizing our data. Let’s start with the interactive visualization using hvPlot
SPLASH Sensor Locations¶
east_river_plot = east_river.hvplot.polygons(height=500,
label='East River Watershed',
color='None',
width=800,
hover=True,
tiles='EsriReference',
xlabel='Longitude',
ylabel='Latitude',
geo=True)
splash_location_plot = splash_locations.hvplot.points(by='Name',
color=hv.Cycle('Category20'),
hover=True,
title='SPLASH Instrument Locations',
geo=True)
splash_overlay = (east_river_plot * splash_location_plot)
splash_overlay
ARM Sensor Sites¶
There are two main sites, including:
The ARM Mobile Facility (AMF) which includes a large number of sensors
The X-Band radar, provided by Colorado State University
east_river_plot = east_river.hvplot.polygons(height=500,
label='East River Watershed',
color='None',
width=800,
hover=True,
tiles='EsriReference',
xlabel='Longitude',
ylabel='Latitude',
geo=True)
arm_doe_plot = arm_doe_locations.hvplot.points(by='Name',
title='ARM-DOE Assets',
hover=True,
geo=True)
sail_overlay = (east_river_plot * arm_doe_plot)
sail_overlay
A Closer Look at the AMF Site¶
We can take a closer look at the AMF siteamf_sensor_locations
amf_sensor_plot = amf_sensor_locations.hvplot.points(x='Lon',
y='Lat',
height=500,
width=800,
tiles='EsriReference',
hover_cols='Name',
geo=True,
color='black',
label='AMF Sensors',
title='AMF Sensor Locations'
)
arm_asset_plot = amf_sensor_plot * arm_doe_plot
Combine our Plots¶
We can plot these two next to each other by adding them together and specifying we want a single column.
(splash_overlay + sail_overlay + arm_asset_plot).cols(1)