{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T03:55:23Z","timestamp":1783655723516,"version":"3.55.0"},"reference-count":40,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2023,9,20]],"date-time":"2023-09-20T00:00:00Z","timestamp":1695168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Jilin Key R&amp;D Program of China","award":["20230201036GX"],"award-info":[{"award-number":["20230201036GX"]}]},{"name":"Jilin Key R&amp;D Program of China","award":["62105331"],"award-info":[{"award-number":["62105331"]}]},{"name":"Jilin Key R&amp;D Program of China","award":["62275114"],"award-info":[{"award-number":["62275114"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["20230201036GX"],"award-info":[{"award-number":["20230201036GX"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["62105331"],"award-info":[{"award-number":["62105331"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["62275114"],"award-info":[{"award-number":["62275114"]}]},{"name":"Qingdao Industrial Experts Program","award":["20230201036GX"],"award-info":[{"award-number":["20230201036GX"]}]},{"name":"Qingdao Industrial Experts Program","award":["62105331"],"award-info":[{"award-number":["62105331"]}]},{"name":"Qingdao Industrial Experts Program","award":["62275114"],"award-info":[{"award-number":["62275114"]}]},{"name":"Taishan Industrial Experts Program","award":["20230201036GX"],"award-info":[{"award-number":["20230201036GX"]}]},{"name":"Taishan Industrial Experts Program","award":["62105331"],"award-info":[{"award-number":["62105331"]}]},{"name":"Taishan Industrial Experts Program","award":["62275114"],"award-info":[{"award-number":["62275114"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recently, considerable efforts have been devoted to the estimation of soil properties using optical payloads mounted on drones or satellites. Nevertheless, many studies focus on diverse pretreatments and modeling techniques, while there continues to be a conspicuous absence of research examining the impact of parameters related to optical remote sensing payloads on predictive performance. The main aim of this study is to evaluate how the spectral resolution and signal-to-noise ratio (SNR) of spectrometers affect the precision of predictions for soil organic matter (SOM) content. For this purpose, the initial soil spectral library was partitioned into to two simulated soil spectral libraries, each of which were individually adjusted with respect to the spectral resolutions and SNR levels. To verify the consistency and generality of our results, we employed four multiple regression models to develop multivariate calibration models. Subsequently, in order to determine the minimum spectral resolution and SNR level without significantly affecting the prediction accuracy, we conducted ANOVA tests on the RMSE and R2 obtained from the independent validation dataset. Our results revealed that (i) the factors significantly affecting SOM prediction performance, in descending order of magnitude, were the SNR levels &gt; spectral resolutions &gt; estimation models, (ii) no substantial difference existed in predictive performance when the spectral resolution fell within 100 nm, and (iii) when the SNR levels exceeded 15%, altering them did not notably affect the SOM predictive performance. This study is expected to provide valuable insights for the design of future optical remote sensing payloads aimed at monitoring large-scale SOM dynamics.<\/jats:p>","DOI":"10.3390\/rs15184623","type":"journal-article","created":{"date-parts":[[2023,9,20]],"date-time":"2023-09-20T21:47:03Z","timestamp":1695246423000},"page":"4623","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Impact of Spectral Resolution and Signal-to-Noise Ratio in Vis\u2013NIR Spectrometry on Soil Organic Matter Estimation"],"prefix":"10.3390","volume":"15","author":[{"given":"Bo","family":"Yu","sequence":"first","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Yuan","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changxiang","family":"Yan","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"Center of Materials Science and Optoelectrics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiawei","family":"Xu","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaoran","family":"Ma","sequence":"additional","affiliation":[{"name":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hu","family":"Dai","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Science and Technology on Vacuum Technology and Physics, Lanzhou Institute of Physics, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.earscirev.2016.01.012","article-title":"A global spectral library to characterize the world\u2019s soil","volume":"155","author":"Behrens","year":"2016","journal-title":"Earth-Sci. 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