plot_burn_locations.py

Per-flight 2x2 analysis plots: burn locations, T4, SWIR, and detection-space scatter.

plot_burn_locations.py - Visualize burn locations, T4, SWIR, and detection error per flight.

Creates one PNG per flight with a 2x2 layout:

Top-left: Fire/false-positive locations on gray background Top-right: T4 brightness temperature (3.9 μm fire channel) Bottom-left: SWIR radiance (2.16 μm solar reflection channel) Bottom-right: T4 vs ΔT scatter with pre-burn false positives overlaid as error reference

The pre-burn flight (24-801-03) is processed first to establish false positive characteristics. Those false positives are then shown in orange on every burn flight’s scatter plot so the error is always visible.

Usage:

python plot_burn_locations.py

plot_burn_locations.plot_single_flight(grid_T4, grid_T11, grid_SWIR, grid_fire, lat_axis, lon_axis, flight_num, comment, day_night, n_files, fp_T4=None, fp_dT=None, preburn_fp_rate=0.0)[source]

Create a 2x2 figure for one flight and save to plots/.

Parameters:
  • grid_SWIR – SWIR radiance at 2.16 μm [W/m²/sr/μm].

  • fp_T4 – Pre-burn false positive T4 and ΔT arrays. When provided, these are overlaid on the scatter plot so the error is visible.

  • fp_dT – Pre-burn false positive T4 and ΔT arrays. When provided, these are overlaid on the scatter plot so the error is visible.

  • preburn_fp_rate – False positive rate from pre-burn flight (FP per valid pixel). Used to estimate error rate on burn flights.

plot_burn_locations.main()[source]