{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T21:17:48Z","timestamp":1768771068320,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2016,12,11]],"date-time":"2016-12-11T00:00:00Z","timestamp":1481414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate spectral calibration of satellite and airborne spectrometers is essential for remote sensing applications that rely on accurate knowledge of center wavelength (CW) positions and slit function parameters (SFP). We present a new in-flight spectral calibration algorithm that retrieves CWs and SFPs across a wide spectral range by fitting a high-resolution solar spectrum and atmospheric absorbers to in-flight radiance spectra. Using a maximum a posteriori optimal estimation approach, the quality of the fit can be improved with a priori information. The algorithm was tested with synthetic spectra and applied to data from the APEX imaging spectrometer over the spectral range of 385\u2013870 nm. CWs were retrieved with high accuracy (uncertainty &lt;0.05 spectral pixels) from Fraunhofer lines below 550 nm and atmospheric absorbers above 650 nm. This enabled a detailed characterization of APEX\u2019s across-track spectral smile and a previously unknown along-track drift. The FWHMs of the slit function were also retrieved with good accuracy (&lt;10% uncertainty) for synthetic spectra, while some obvious misfits appear for the APEX spectra that are likely related to radiometric calibration issues. In conclusion, our algorithm significantly improves the in-flight spectral calibration of APEX and similar spectrometers, making them better suited for the retrieval of atmospheric and surface variables relying on accurate calibration.<\/jats:p>","DOI":"10.3390\/rs8121017","type":"journal-article","created":{"date-parts":[[2016,12,12]],"date-time":"2016-12-12T14:43:57Z","timestamp":1481553837000},"page":"1017","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["An Algorithm for In-Flight Spectral Calibration of Imaging Spectrometers"],"prefix":"10.3390","volume":"8","author":[{"given":"Gerrit","family":"Kuhlmann","sequence":"first","affiliation":[{"name":"Empa, Swiss Federal Laboratories for Materials Science and Technology, CH-8600 D\u00fcbendorf, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4283-2484","authenticated-orcid":false,"given":"Andreas","family":"Hueni","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratories, University of Z\u00fcrich, CH-8057 Z\u00fcrich, Switzerland"}]},{"given":"Alexander","family":"Damm","sequence":"additional","affiliation":[{"name":"Remote Sensing Laboratories, University of Z\u00fcrich, CH-8057 Z\u00fcrich, Switzerland"}]},{"given":"Dominik","family":"Brunner","sequence":"additional","affiliation":[{"name":"Empa, Swiss Federal Laboratories for Materials Science and Technology, CH-8600 D\u00fcbendorf, Switzerland"}]}],"member":"1968","published-online":{"date-parts":[[2016,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2015.06.011","article-title":"Special issue on the Hyperspectral Infrared Imager (HyspIRI): Emerging science in terrestrial and aquatic ecology, radiation balance and hazards","volume":"167","author":"Hochberg","year":"2015","journal-title":"Remote Sens. 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