Drone hyperspectral → NEON reference → Landsat reflectance
Drone to Landsatthrough NEON
Make hyperspectral reflectance comparable across scales.
SpectralBridge uses NEON airborne hyperspectral observations as the translating reference between fine-scale drone measurements and Landsat bandspace. Its correction, spectral convolution, tabular extraction, and QA steps keep every scientific decision inspectable and reproducible.
Drone → NEON → Landsat
Why it exists
One NEON-mediated bridge. Three observing scales.
Relate fine-resolution drone measurements to Landsat-compatible bands through NEON's airborne hyperspectral reference without hiding the corrections, response functions, provenance, or quality evidence along the way.
The system at a glance
Three technical views. Read them one at a time.
The original scientific figure is separated into enlarged panels here. The plots, wavelength ranges, processing stages, and translation relationships remain unchanged; the surrounding text provides a readable path through them.
Measure at three scales.
NEON airborne imaging spectroscopy, MicaSense UAS observations, and Landsat Collection 2 NBAR each sample reflectance differently. The first panel keeps their spectral ranges and sampling patterns visible together.
Why cross-sensor calibration matters →
Correct before you compare.
The processing panel follows input reflectance through topographic correction, BRDF correction, spectral convolution, and empirical calibration. Keeping these operations explicit is what makes the translation inspectable.
Walk through the full pipeline →Use NEON as the hyperspectral anchor.
Paired synthetic and observed measurements define empirical translations among the three sensor spaces. NEON's dense airborne spectrum supplies the central reference for relating drone-scale measurements to Landsat.
Inspect sensor harmonization →- DeterministicSame input, same output
- RestartableResume from any stage
- VersionedCode, parameters, and data tracked
- Provenance trackedInputs, models, and outputs
- Open and reproducibleTransparent and extensible
Choose your way in
Start with what you need today.
Learn
Follow one focused vignette for each module—or run the complete workflow.
Browse the vignettes → 02Validate
See the input variations, explicit checks, and diagnostics behind reliability claims.
Inspect the evidence → 03Reference
Look up stage contracts, filenames, configuration, schemas, algorithms, and APIs.
Open technical details →The scientific story
Raw signal in. Comparable evidence out.
Each stage writes validated files that the next stage can understand—and a future rerun can safely reuse.
Evidence, not mystery
Every transformation should leave a trail.
Validation campaigns record input variation, expected behavior, observed diagnostics, runtime, provenance, and failures. QA panels turn those records into something scientists can inspect.
See how SpectralBridge is validated →Already halfway there?
Carry on from the files you have.
The pipeline validates existing artifacts and resumes at the first missing or invalid stage.
Carry On My Wayward Son →Ready when you are