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Gabbard Diagrams

A Gabbard diagram plots orbital period versus apogee and perigee altitude, providing a unique visualization for analyzing debris clouds, satellite breakups, and orbital constellations. Each object appears as two points: one for apogee altitude and one for perigee altitude, both at the same orbital period. This creates a characteristic pattern that reveals the distribution and evolution of orbital populations.

Interactive Gabbard Diagram (Plotly)

The plotly backend allows you to zoom into specific regions and hover over points to see exact values.

Plot Source
gabbard_plotly.py
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"""
Gabbard Diagram Example - Plotly Backend

This script demonstrates how to create an interactive Gabbard diagram using the plotly backend.
A Gabbard diagram plots orbital period vs apogee/perigee altitude, useful for analyzing
debris clouds or satellite constellations.
"""

import os
import pathlib
import sys
import brahe as bh

# Add plots directory to path for importing brahe_theme
sys.path.insert(0, str(pathlib.Path(__file__).parent.parent.parent))
from brahe_theme import save_themed_html

# Configuration
SCRIPT_NAME = pathlib.Path(__file__).stem
OUTDIR = pathlib.Path(os.getenv("BRAHE_FIGURE_OUTPUT_DIR", "./docs/figures/"))
os.makedirs(OUTDIR, exist_ok=True)

# Initialize EOP data
bh.initialize_eop()

# Get Ephmeris and debris for major events:
cosmos_1408_debris = bh.celestrak.get_tles_as_propagators("cosmos-1408-debris", 60.0)
fengyun_debris = bh.celestrak.get_tles_as_propagators("fengyun-1c-debris", 60.0)
iridium_debris = bh.celestrak.get_tles_as_propagators("iridium-33-debris", 60.0)
cosmos_2251_debris = bh.celestrak.get_tles_as_propagators("cosmos-2251-debris", 60.0)
all_debris = cosmos_1408_debris + fengyun_debris + iridium_debris + cosmos_2251_debris

print(f"Cosmos 1408 debris objects: {len(cosmos_1408_debris)}")
print(f"Fengyun-1C debris objects: {len(fengyun_debris)}")
print(f"Iridium 33 debris objects: {len(iridium_debris)}")
print(f"Cosmos 2251 debris objects: {len(cosmos_2251_debris)}")
print(f"Total debris objects loaded: {len(all_debris)}")

# Get epoch of first debris object
epoch = all_debris[0].epoch

# Get ISS ephemeris for reference altitude line
iss = bh.celestrak.get_tle_by_id_as_propagator(25544, 60.0, "active")
iss_state = iss.state_eci(epoch)
iss_oe = bh.state_eci_to_koe(iss_state, bh.AngleFormat.RADIANS)
iss_altitude_km = (iss_oe[0] - bh.R_EARTH) / 1e3  # Convert to km

print(f"ISS altitude at epoch: {iss_altitude_km:.1f} km")

# Create Gabbard diagram
fig = bh.plot_gabbard_diagram(all_debris, epoch, backend="plotly")

# Add ISS altitude reference line
fig.add_hline(
    y=iss_altitude_km,
    line_dash="dash",
    line_color="orange",
    line_width=2,
    annotation_text=f"ISS Altitude ({iss_altitude_km:.1f} km)",
    annotation_position="right",
)

# Save themed HTML files
light_path, dark_path = save_themed_html(fig, OUTDIR / SCRIPT_NAME)
print(f"✓ Generated {light_path}")
print(f"✓ Generated {dark_path}")

Static Gabbard Diagram (Matplotlib)

The matplotlib backend produces publication-quality figures for research papers and technical reports.

Gabbard Diagram Gabbard Diagram
Plot Source
gabbard_matplotlib.py
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"""
Gabbard Diagram Example - Matplotlib Backend

This script demonstrates how to create a Gabbard diagram using the matplotlib backend.
A Gabbard diagram plots orbital period vs apogee/perigee altitude, useful for analyzing
debris clouds or satellite constellations.
"""

import os
import pathlib
import brahe as bh
import matplotlib.pyplot as plt

# Configuration
SCRIPT_NAME = pathlib.Path(__file__).stem
OUTDIR = pathlib.Path(os.getenv("BRAHE_FIGURE_OUTPUT_DIR", "./docs/figures/"))
os.makedirs(OUTDIR, exist_ok=True)

# Initialize EOP data
bh.initialize_eop()

# Get Ephmeris and debris for major events:
cosmos_1408_debris = bh.celestrak.get_tles_as_propagators("cosmos-1408-debris", 60.0)
fengyun_debris = bh.celestrak.get_tles_as_propagators("fengyun-1c-debris", 60.0)
iridium_debris = bh.celestrak.get_tles_as_propagators("iridium-33-debris", 60.0)
cosmos_2251_debris = bh.celestrak.get_tles_as_propagators("cosmos-2251-debris", 60.0)
all_debris = cosmos_1408_debris + fengyun_debris + iridium_debris + cosmos_2251_debris

print(f"Cosmos 1408 debris objects: {len(cosmos_1408_debris)}")
print(f"Fengyun-1C debris objects: {len(fengyun_debris)}")
print(f"Iridium 33 debris objects: {len(iridium_debris)}")
print(f"Cosmos 2251 debris objects: {len(cosmos_2251_debris)}")
print(f"Total debris objects loaded: {len(all_debris)}")

# Get epoch of first debris object
epoch = all_debris[0].epoch

# Get ISS ephemeris for reference altitude line
iss = bh.celestrak.get_tle_by_id_as_propagator(25544, 60.0, "active")
iss_state = iss.state_eci(epoch)
iss_oe = bh.state_eci_to_koe(iss_state, bh.AngleFormat.RADIANS)
iss_altitude_km = (iss_oe[0] - bh.R_EARTH) / 1e3  # Convert to km

print(f"ISS altitude at epoch: {iss_altitude_km:.1f} km")

# Create Gabbard diagram in light mode
fig = bh.plot_gabbard_diagram(all_debris, epoch, backend="matplotlib")

# Add ISS altitude reference line
ax = fig.get_axes()[0]
ax.axhline(
    y=iss_altitude_km,
    color="green",
    linestyle="--",
    linewidth=2,
    label=f"ISS Altitude ({iss_altitude_km:.1f} km)",
)
ax.legend()

# Save light mode figure
light_path = OUTDIR / f"{SCRIPT_NAME}_light.svg"
fig.savefig(light_path, dpi=300, bbox_inches="tight")
print(f"✓ Generated {light_path}")
plt.close(fig)

# Create Gabbard diagram in dark mode
with plt.style.context("dark_background"):
    fig = bh.plot_gabbard_diagram(all_debris, epoch, backend="matplotlib")

    # Set background color to match Plotly dark theme
    fig.patch.set_facecolor("#1c1e24")
    for ax in fig.get_axes():
        ax.set_facecolor("#1c1e24")

    # Add ISS altitude reference line
    ax = fig.get_axes()[0]
    ax.axhline(
        y=iss_altitude_km,
        color="orange",
        linestyle="--",
        linewidth=2,
        label=f"ISS Altitude ({iss_altitude_km:.1f} km)",
    )
    ax.legend()

    # Save dark mode figure
    dark_path = OUTDIR / f"{SCRIPT_NAME}_dark.svg"
    fig.savefig(dark_path, dpi=300, bbox_inches="tight")
    print(f"✓ Generated {dark_path}")
    plt.close(fig)

Understanding the Diagram

Reading the Plot

  • X-axis: Orbital period (minutes or hours)
  • Y-axis: Altitude (km)
  • Each object creates TWO points:
    • Upper point: Apogee altitude
    • Lower point: Perigee altitude

Interpreting Patterns

Tight vertical pairs: Low eccentricity (near-circular orbits)

Wide vertical separation: High eccentricity (elliptical orbits)

Tips

  • Use backend="plotly" to identify outliers and explore specific objects interactively
  • Add reference lines for altitude constraints (e.g., ISS orbit, debris-heavy regions)

See Also