Benchmark Results
Six models evaluated across 3 real EnMAP scenes with 5 random seeds each. These are frozen scientific results — not live analysis outputs. For a live run, go to Intelligence → Run Analysis.
SCIENTIFIC INTERPRETATION
Competitive numerical result
AgriSpectra-Q has the highest mean F1 (96.40%) among all six evaluated systems.
Statistical superiority over HSI-RF not established
Bootstrap 95% CI [−0.0012, +0.0027] crosses zero. Not statistically significant.
Benchmark target is a Spectral Anomaly Proxy — not independently labelled disease or pest outcome.
TABLE 1
Six-Model Benchmark
| Model | Mean F1 | PR-AUC | ROC-AUC |
|---|---|---|---|
AgriSpectra-QOur System | 96.40% | 99.47% | 99.87% |
Adaptive Classical | 96.34% | 99.47% | 99.86% |
HSI-RF | 96.31% | 99.49% | 99.87% |
48-band XGBoost | 95.22% | 99.23% | 99.80% |
Spectral XGBoost | 94.78% | 99.24% | 99.81% |
Current Hybrid | 89.98% | 96.16% | 98.75% |
TABLE 2
AgriSpectra-Q — Per-Scene Results
| Scene | F1 | Precision | Recall | ROC-AUC |
|---|---|---|---|---|
| Scene 01 (DT0000205230) | 98.47% | 98.23% | 98.73% | 99.98% |
| Scene 02 | 95.42% | 95.80% | 95.10% | 99.83% |
| Scene 03 | 95.30% | 94.81% | 95.83% | 99.79% |
KEY FINDINGS
What the Benchmark Tells Us
AgriSpectra-Q achieves 96.40% mean F1 — highest numerical result among all six evaluated systems.
Scene 01 (DT0000205230) delivers 98.47% F1, reflecting high spectral contrast in the Al Ain oasis region.
Calibration ECE of 0.73% after post-hoc scaling — well-calibrated probabilities for decision support.
At 10% inspection budget, the system achieves ~49% positive recall — ~5× better than random sampling.
Ablation studies confirm the quantum-inspired component provides measurable contribution.
Paired bootstrap CI [−0.0012, +0.0027] vs HSI-RF at n=10,000 replicates.
VALIDATION METHODOLOGY
Statistical stability across initialisation variance
No simulated data — all results on actual EO imagery
Rigorous significance testing for model comparisons
Run a live spectral-priority analysis
Apply the live engine to real EnMAP scenes and generate georeferenced priority zones.