Scenario kind pagesEdit on GitHubSource: docs/kinds/by-kind/eo-radiometry.md

eo-radiometry (scenario kind)

Scenario kind of the engine v0.38.0, family Mission analysis, links and space operations. Advisory: analysis output from a research and engineering tool, not type-approved navigation equipment and not a safety-of-life service. Every label here is the engine's or the verification matrix's; a kind is MODELLED unless the matrix says otherwise (how a label is earned: the README's Evidence section).

What it does#

Nadir imager radiometry and image quality: at-aperture radiance of a Lambertian scene, the camera equation, signal and shot/dark/read/quantisation noise and SNR; the system MTF at Nyquist (diffraction x detector x smear x jitter), the relative edge response from it, Q = lambda F/p and the GIQE version 4 NIIRS with no MTF compensation. MODELLED.

One run of scenarios/eo-radiometry.toml summarises as: eo-radiometry: GSD 0.76 m, Q 1.06, SNR 39 (well 6 %), MTF@Nyquist 0.212, RER 0.573, GIQE4 NIIRS 4.27 (MODELLED)

Inputs#

From the schema (kshana kinds --json):

  • Required fields: none
  • Optional fields: altitude_m, focal_length_m, aperture_m, pixel_pitch_um, wavelength_um, bandwidth_um, fill_factor, smear_px, jitter_px_rms, reflectance, solar_irradiance_w_m2_um, sun_zenith_deg, atmospheric_transmittance, path_radiance_w_m2_sr_um, optics_transmittance, integration_s, quantum_efficiency, dark_current_e_s, read_noise_e, full_well_e, adc_bits

The example scenarios/eo-radiometry.toml sets, among others:

Field Value Unit
adc_bits 12 count
altitude_m 500000 m
aperture_m 0.4 m
atmospheric_transmittance 0.7 1
bandwidth_um 0.2 um
dark_current_e_s 50 e/s
fill_factor 1 1
focal_length_m 3.6 m
full_well_e 30000 e
integration_s 5.0000e-4 s
jitter_px_rms 0.1 px
kind eo-radiometry text

Run it#

kshana scenarios/eo-radiometry.toml

What it gives#

The scalar results of that run, with the units the engine states:

Result Value Unit
cutoff_cy_mm 170.940171 cycles/mm
f_number 9 1
focal_plane_irradiance_w_m2_um 0.306889 W/m^2/um
gsd_m 0.763889 m
inputs.adc_bits 12 count
inputs.altitude_m 500000 m
inputs.aperture_m 0.4 m
inputs.atmospheric_transmittance 0.7 1
inputs.bandwidth_um 0.2 um
inputs.dark_current_e_s 50 e/s

Result label (the engine's): MODELLED — nadir imager radiometry (Lambertian scene, camera equation, shot/dark/read/quantisation noise), system MTF at Nyquist (diffraction x detector x smear x jitter), relative edge response, Q = lambda F/p and GIQE 4 NIIRS with no MTF compensation; the NIIRS is an empirical regression on modell

The chart the engine writes for scenarios/eo-radiometry.toml, kind eo-radiometry

Evidence#

MODELLED: the verification matrix rows that name this kind.

  • MODELLED Nadir imager signal-to-noise budget (Lambertian scene radiance, camera equation, shot, dark, read and quantisation noise), the system MTF at Nyquist as the product of unobscured-aperture diffraction, detector aperture, linear smear and Gaus

The rows the run itself exercised, with the oracle the matrix gives each (the public sources are named there):

  • MODELLED Deterministic, scenario-hashed, SBOM + cross-platform golden gates. Oracle (ExternalDataset): SBOM conformance to the official CycloneDX 1.5 JSON Schema (+ valid SPDX identifiers) — an external published standard, zero validation errors over the full dependency graph; the FoM-determinism / byte-reproducibility part remains a pinned self-consistency check, so the row stays MODELLED
  • MODELLED Nadir imager signal-to-noise budget (Lambertian scene radiance, camera equation, shot, dark, read and quantisation noise), the system MTF at Nyquist as the prod. Oracle (InternalConsistency): Closed forms: the diffraction MTF at half cutoff, the one-pixel ramp edge of a pure detector aperture (RER 1), the normal-CDF edge of a Gaussian blur (RER = erf(0.5/(sigma sqrt 2))), shot-noise scaling, and the GIQE 4 coefficients as published (Leachtenauer et al., Applied Optics 36(32), 1997). WHAT IS NOT: no external imager, measured MTF or rated image has been compared; the GIQE is an empirical regression with its

Limitations#

What the run's own report says is not modelled or not validated:

  • MODELLED — nadir imager radiometry (Lambertian scene, camera equation, shot/dark/read/quantisation noise), system MTF at Nyquist (diffraction x detector x smear x jitter), relative edge response, Q = lambda F/p and GIQE 4 NIIRS with no MTF compensation; the NIIRS is an empirical regression on modelled inputs, not a rated image (result label)
  • MODELLED. (kind catalogue (kshana kinds --json))
  • Nadir imager radiometry and image quality for an ILLUSTRATIVE small Earth-observation camera (no operator's design): 0.40 m aperture, 3.6 m focal length (F/9), 5.5 um pixels, from 500 km. The run gives the signal-to-noise budget of a 15 % reflectance scene, the system MTF at Nyquist, the relative edge response and the GIQE version 4 NIIRS. MODELLED: the NIIRS is an empirical regression evaluated on modelled inputs, n (scenario file comment, lines 1 to 5)
  • Reproducibility & software assurance is MODELLED, not validated: a sub-claim is externally checked, but the whole capability composes modelled pieces, so the capability stays Modelled. (verification matrix (docs/MODELLED-RATIONALE.md))
  • Electro-optical imager radiometry, MTF, relative edge response and GIQE 4 NIIRS is MODELLED, not validated: checked against its own closed-form / analytic identity — catches transcription and coefficient errors, but is not an external oracle. (verification matrix (docs/MODELLED-RATIONALE.md))

See also#