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Charles M. Bachmann

Publications and source records attributed to Charles M. Bachmann.

4 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Shape from spectra

We introduce a new unified atmospheric–topographic correction approach that estimates surface geometry directly from the radiance measurement. Surface topography influences the at-sensor radiance measurement, making precise topography modeling critical in applications like vegetation or snow studies in mountainous terrain. Currently, elevation maps are used to derive topographic variables such as the slope and sky-view factor. This process is error-prone since static global digital elevation models do not generally achieve the accuracy required, and even minor mismatches in spatial resolution can introduce significant artifacts in downstream processing. Here we demonstrate that it is possible to estimate topographic parameters directly from spectral data, ensuring perfect physical consistency, temporal coincidence, and spatial alignment. We present experiments estimating topographic slope in two scenes in Southern California, with data from NASA’s Next Generation Airborne Visible/Near Infrared Imaging Spectrometer (AVIRIS-NG). We compared our radiance-based estimates against high-resolution lidar datasets. Our initial validation result showed a correlation of R 2 = 0.864 (n = 160) over the homogeneous surface of Beckman Auditorium’s cone-shaped roof on the Caltech campus in Pasadena, California. We then validate the model over a larger study site near Santa Clarita, California, finding R 2 = 0.923 (n = 40,000) in a 350 x 350m area. The accuracy of our model estimates, combined with its systematic advantages over the alternative, show the potential of the approach for use in both airborne campaigns and orbital missions.

Nimrod Carmon↗
NASA NTRSDate not supplied

Goniometric and Polarized Imaging Spectroscopic Lab Measurements of Spacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using directional reflectance spectroscopy and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation (MLI) commonly used on spacecraft for initial measurements. The directional spectral data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a lab and field goniometer incorporating two AnalyticalSpectral Device (ASD) spectrometers, a small Lab sphere integrating sphere also paired with an ASD spectrometer, and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer measures spectral bi-directional reflectance factor (BRF) data over a broad range from 350−2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. With the same spectral capabilities, the integrating sphere measures hemispherical-directional reflectance (HDR) in a 45◦-nadir configuration. The Headwall imager covers a spectral range from 400−1000 nm with 1.6 nm spectral resolution.Our initial BRF measurements show interference effects for both materials typically observed with thin films and high infrared reflectivity. In contrast, the interference effects are not present in the HDR measurements of the MLI likely due to the interference effects being averaged out over the reflecting hemisphere. Spatially resolved polarization ratio maps show variability across the materials due to the varying surface structure. We outline a plan for expanding our analysis to a broader range of materials to characterize their directional reflectance spectroscopy.

Chris H. Lee↗