ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XI-1-2026
https://doi.org/10.5194/isprs-annals-XI-1-2026-61-2026
https://doi.org/10.5194/isprs-annals-XI-1-2026-61-2026
03 Jul 2026
 | 03 Jul 2026

First Field Validation of a New VNIR–SWIR-Based Six-Band Multi-Camera System for UAVs over Winter Wheat

Alexander Jenal, Fabian Reddig, Andreas Bolten, Leon Vehlken, Hubert Hüging, Thuy Huu Nguyen, Jens Bongartz, and Georg Bareth

Keywords: shortwave infrared, multispectral, empirical line calibration, calibration/validation, precision agriculture, crop monitoring

Abstract. Shortwave infrared (SWIR) UAV imaging remains uncommon despite its sensitivity to canopy water and protein. We report, to our knowledge, the first field validation of a six-band, simultaneously exposed VNIR/SWIR multicamera for plot-scale winter wheat. The payload used narrow bandpass filters at 910, 980, 1100, 1200, 1510, and 1650 nm (FWHM 10–12 nm) and was flown at 30 m AGL, yielding 4 cm GSD. Radiometric calibration used in-flight empirical line calibration with an in-scene gray panel set, followed by independent validation on a material-distinct gray set. ASD spectroradiometer measurements were convolved with Gaussian proxy spectral response functions matched to the nominal filter passbands. Empirical line fits were near-perfect (R2 ≈ 1.000; RMSE = 0.003–0.009). Independent panel validation showed near-unity slopes for five bands from 980–1650 nm (R2 = 0.998–0.999; RMSE = 0.005–0.013). Across 36 canopy plot ROIs, camera-to-ASD agreement remained strong for five bands, with slopes of 0.943–1.079, R2 = 0.58–0.85, and RMSE = 0.010–0.023. Two SWIR normalized ratio indices showed tight cross-sensor agreement: NRI[1100,1200] (R2 ≈ 0.93; RMSE ≈ 0.010) and NRI[1650,1510] (R2 ≈ 0.90; RMSE ≈ 0.017–0.018). Post-hoc filter transmittance measurements revealed secondary long-wavelength throughput in the 910 nm channel, causing compressed slopes and elevated error (MAPE ≈ 33%); this band was excluded from accuracy claims. Panel-anchored, bandpass-aware calibration enables quantitative UAV SWIR reflectance and robust SWIR indices for precision agriculture applications. The workflow also identifies hardware-specific failure modes, supporting reproducible validation and informed redesign of filter-reconfigurable SWIR payloads.

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