Visualizing PACE data interactively with HyperCoast¶

This notebook demonstrates how to visualize Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) data interactively with HyperCoast.

In [1]:

# %pip install "hypercoast[extra]"

# %pip install "hypercoast[extra]"

In [2]:

import hypercoast

import hypercoast

Download a sample PACE data file from here.

In [3]:

url = "https://github.com/opengeos/datasets/releases/download/hypercoast/PACE_OCI.20240730T181157.L2.OC_AOP.V2_0.NRT.nc"

url = "https://github.com/opengeos/datasets/releases/download/hypercoast/PACE_OCI.20240730T181157.L2.OC_AOP.V2_0.NRT.nc"

In [4]:

filepath = "data/PACE_OCI.20240730T181157.L2.OC_AOP.V2_0.NRT.nc"
hypercoast.download_file(url, filepath)

filepath = "data/PACE_OCI.20240730T181157.L2.OC_AOP.V2_0.NRT.nc" hypercoast.download_file(url, filepath)

data/PACE_OCI.20240730T181157.L2.OC_AOP.V2_0.NRT.nc already exists. Skip downloading. Set overwrite=True to overwrite.

Out[4]:

'/home/runner/work/HyperCoast/HyperCoast/docs/examples/data/PACE_OCI.20240730T181157.L2.OC_AOP.V2_0.NRT.nc'

Let's make a scatter plot of the pixel locations so we can see the irregular spacing.

In [5]:

plot = hypercoast.view_pace_pixel_locations(filepath, step=20)

plot = hypercoast.view_pace_pixel_locations(filepath, step=20)

Load the dataset as a xarray.Dataset object.

In [6]:

dataset = hypercoast.read_pace(filepath)

dataset = hypercoast.read_pace(filepath)

Visualize selected bands of the dataset.

In [7]:

hypercoast.viz_pace(dataset, wavelengths=[500, 510, 520, 530], ncols=2)

hypercoast.viz_pace(dataset, wavelengths=[500, 510, 520, 530], ncols=2)

Add projection.

In [8]:

hypercoast.viz_pace(dataset, wavelengths=[500, 510, 520, 530], ncols=2, crs="default")

hypercoast.viz_pace(dataset, wavelengths=[500, 510, 520, 530], ncols=2, crs="default")

Plot a spectral signature.

In [9]:

latitude = 29.9307
longitude = -87.9106
hypercoast.extract_pace(dataset, latitude, longitude, return_plot=True)

latitude = 29.9307 longitude = -87.9106 hypercoast.extract_pace(dataset, latitude, longitude, return_plot=True)

Out[9]:

[<matplotlib.lines.Line2D at 0x7fc643c6d0a0>]

Plot multiple spectral signatures.

In [10]:

latitude = (29.49, 29.50)
longitude = (-88.10, -88.00)
hypercoast.filter_pace(dataset, latitude, longitude, return_plot=True)

latitude = (29.49, 29.50) longitude = (-88.10, -88.00) hypercoast.filter_pace(dataset, latitude, longitude, return_plot=True)

Single-band visualization.

In [11]:

m = hypercoast.Map()
m.add_basemap("Hybrid")
wavelengths = [450]
m.add_pace(dataset, wavelengths, colormap="jet", vmin=0, vmax=0.02, layer_name="PACE")
m.add_colormap(cmap="jet", vmin=0, vmax=0.02, label="Reflectance")
m.add("spectral")
m

m = hypercoast.Map() m.add_basemap("Hybrid") wavelengths = [450] m.add_pace(dataset, wavelengths, colormap="jet", vmin=0, vmax=0.02, layer_name="PACE") m.add_colormap(cmap="jet", vmin=0, vmax=0.02, label="Reflectance") m.add("spectral") m

Out[11]:

Multiple-band visualization.

In [12]:

m = hypercoast.Map()
m.add_basemap("Hybrid")
wavelengths = [450, 550, 650]
m.add_pace(
    dataset, wavelengths, indexes=[3, 2, 1], vmin=0, vmax=0.02, layer_name="PACE"
)
m.add("spectral")
m

m = hypercoast.Map() m.add_basemap("Hybrid") wavelengths = [450, 550, 650] m.add_pace( dataset, wavelengths, indexes=[3, 2, 1], vmin=0, vmax=0.02, layer_name="PACE" ) m.add("spectral") m

Out[12]: