Appendix H — Homework Exercise 8: Generation and Interpretation of an Interferogram using Sentinel-1 Imagery

The following data were acquired from Sentinel-1 on April 23, 2018, from 16:15:24 to 16:15:51 over the region of Hawaii. Use the provided code to load and plot the preprocessed SAR interferometric data. Observe, analyse, and visually interpret the results.

from pathlib import Path
from io import BytesIO
import base64

import intake
import xarray as xr
import matplotlib.pyplot as plt
import hvplot.xarray  # noqa: F401
import seaborn as sns
import holoviews as hv  # noqa: F401
import folium
from matplotlib.colors import ListedColormap

from mrs.catalog import get_intake_url

H.1 Load the data

url = get_intake_url()
cat = intake.open_catalog(url)
ds = cat.ex8.read().compute()
ds

https://git.geo.tuwien.ac.at/public_projects/microwave-remote-sensing/-/raw/dev-exs/microwave-remote-sensing.yml

H.2 Plotting the data

step = 4

cmap_hls = sns.color_palette("hls", n_colors=256).as_hex()

ds = ds.where(ds != 0)
igf_data = ds.PhaseBand.isel(x=slice(0, -1, step), y=slice(0, -1, step))
coh_da = ds.CohBand.isel(x=slice(0, -1, step), y=slice(0, -1, step))

igf_plot = igf_data.hvplot.image(
    x="x",
    y="y",
    cmap=cmap_hls,
    width=600,
    height=600,
    dynamic=False
)


coh_plot = coh_da.hvplot.image(
    x="x",
    y="y",
    cmap="viridis",
    width=600,
    height=600,
    dynamic=False,
).opts(clim=(0, 1))

(igf_plot + coh_plot).opts(shared_axes=True)

H.3 Question 1

Please refer to the above plots. Which of the following statements are correct?

The image on the left shows a phase interferogram.
The image on the right shows an amplitude interferogram, also called coherence.
The image on the right shows a RTC sigma nougth backscatter.

Focus on the left plot. Which of the following statements are correct?

The fringe pattern could be indicative of both local surface topography and ground deformation.
The circular fringe pattern on the left indicates an uplifiting displacement.
The circular fringe pattern on the left indicates a sinking displacement.

Don’t change anything in the next cell, besides the step for sampling (skipping pixels in the plot), if the plotting takes too long to finish.

cmap_hls = ListedColormap(sns.color_palette("hls", 256).as_hex())


def array_to_img(data_array, cmap="viridis"):
    """Convert an xarray DataArray to a base64-encoded PNG image."""
    fig, ax = plt.subplots(figsize=(6, 6), dpi=600)
    data_array.plot(ax=ax, cmap=cmap, add_colorbar=False, add_labels=False)
    ax.set_axis_off()
    buf = BytesIO()
    plt.savefig(
        buf, format="png", bbox_inches="tight", pad_inches=0, transparent=True
    )
    plt.close(fig)
    return base64.b64encode(buf.getvalue()).decode("utf-8")


# Prepare data
step = 1
igf_image = array_to_img(
    ds.PhaseBand.isel(x=slice(0, -1, step), y=slice(0, -1, step)),
    cmap=cmap_hls,
)
coh_image = array_to_img(
    ds.CohBand.isel(x=slice(0, -1, step), y=slice(0, -1, step))
)

# Map setup and overlay function
bounds = [
    [float(ds.y.min()), float(ds.x.min())],
    [float(ds.y.max()), float(ds.x.max())],
]
m = folium.Map(location=[ds.y.median(), ds.x.median()], zoom_start=10)
folium.TileLayer(
    tiles=(
        "https://server.arcgisonline.com/ArcGIS/rest/"
        + "services/World_Imagery/MapServer/tile/{z}/{y}/{x}"
    ),
    attr="Tiles &copy; Esri &mdash; Source: Esri, DeLorme, NAVTEQ",
    name="ESRI World Imagery",
).add_to(m)


def overlay_image(map_obj, img_base64, bounds, name):
    folium.raster_layers.ImageOverlay(
        image=f"data:image/png;base64,{img_base64}",
        bounds=bounds,
        opacity=0.65,
        name=name,
    ).add_to(map_obj)


# Add images and controls
overlay_image(m, igf_image, bounds, "IGF Data")
overlay_image(m, coh_image, bounds, "Coherence Data")
folium.LayerControl().add_to(m)

m

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

H.4 Question 2

Please refer to the above plot, select the “IGF Data” layer, and select the correct statements:

The interferogram above depicts ground deformation due to an earthquake event.
The interferogram above depicts ground deformation due to a volcanic eruption event.
The interferogram above does not show evidence of ground deformation.

Please refer to the above plot, select the “Coherence Data” layer, and select the correct statements:

The coherence is high (bright color) over urban areas.
The coherence is low (dark color) over forested areas.
The coherence is high over bare soil (non-forested areas).