{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,26]],"date-time":"2025-10-26T14:45:29Z","timestamp":1761489929882,"version":"build-2065373602"},"reference-count":55,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2016,4,6]],"date-time":"2016-04-06T00:00:00Z","timestamp":1459900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Basic Research Program of China","award":["2013CB733406"],"award-info":[{"award-number":["2013CB733406"]}]},{"name":"the Natural Science Foundation of China","award":["41571409","41541043"],"award-info":[{"award-number":["41571409","41541043"]}]},{"name":"the Fundamental Research Funds for the Central Universities","award":["2014kJJCA02"],"award-info":[{"award-number":["2014kJJCA02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators\u2014depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs\/radiance\u2014to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value\/the base value in the oxygen absorption depth in the O2-A and O2-B bands (111.4% and 77.1% in the O2-A band; and 27.5% and 32.6% in the O2-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R2 = 0.91 for Damm vs. SCOPE SIF; R2 = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence.<\/jats:p>","DOI":"10.3390\/s16040480","type":"journal-article","created":{"date-parts":[[2016,4,6]],"date-time":"2016-04-06T12:54:18Z","timestamp":1459947258000},"page":"480","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5160-4574","authenticated-orcid":false,"given":"Zhuoya","family":"Ni","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Key Laboratory of Environmental Remote Sensing and Digital City, Beijing Normal University, Beijing 100875, China"},{"name":"ICube, CNRS, Universit\u00e9 de Strasbourg, 300 Boulevard S\u00e9bastien Brant, CS10413, Illkirch 67412, France"}]},{"given":"Zhigang","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Key Laboratory of Environmental Remote Sensing and Digital City, Beijing Normal University, Beijing 100875, China"}]},{"given":"Zhao-Liang","family":"Li","sequence":"additional","affiliation":[{"name":"ICube, CNRS, Universit\u00e9 de Strasbourg, 300 Boulevard S\u00e9bastien Brant, CS10413, Illkirch 67412, France"},{"name":"Key Laboratory of Agri-informatics, Ministry of Agriculture\/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"}]},{"given":"Fran\u00e7oise","family":"Nerry","sequence":"additional","affiliation":[{"name":"ICube, CNRS, Universit\u00e9 de Strasbourg, 300 Boulevard S\u00e9bastien Brant, CS10413, Illkirch 67412, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5843-3106","authenticated-orcid":false,"given":"Hongyuan","family":"Huo","sequence":"additional","affiliation":[{"name":"College of Urban and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2070-3278","authenticated-orcid":false,"given":"Rui","family":"Sun","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Key Laboratory of Environmental Remote Sensing and Digital City, Beijing Normal University, Beijing 100875, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4377-8560","authenticated-orcid":false,"given":"Peiqi","family":"Yang","sequence":"additional","affiliation":[{"name":"ITC-Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede 7514AE, The Netherlands"}]},{"given":"Weiwei","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Key Laboratory of Environmental Remote Sensing and Digital City, Beijing Normal University, Beijing 100875, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,4,6]]},"reference":[{"key":"ref_1","unstructured":"Lichtenthaler, H., and Buschmann, C. 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