{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T07:30:57Z","timestamp":1769844657912,"version":"3.49.0"},"reference-count":46,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research and Development Project from Hebei Province of China","award":["21351803D"],"award-info":[{"award-number":["21351803D"]}]},{"name":"Key Research and Development Project from Hebei Province of China","award":["42075129"],"award-info":[{"award-number":["42075129"]}]},{"name":"National Natural Science Foundation of China","award":["21351803D"],"award-info":[{"award-number":["21351803D"]}]},{"name":"National Natural Science Foundation of China","award":["42075129"],"award-info":[{"award-number":["42075129"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The accurate prediction of PM2.5 concentrations is important for environmental protection. The accuracy of the commonly used prediction methods is not high; so, this paper proposes a PM2.5 concentration prediction method based on a hybrid learning model. The Top-of-Atmosphere Reflectance (TOAR), PM2.5 data decomposed by wavelets, and meteorological data were used as input features to build an integrated prediction model using random forest and LightGBM, which was applied to PM2.5 concentration prediction in the Beijing\u2013Tianjin\u2013Hebei region. The practical application showed that the proposed method using TOAR, incorporating wavelet decomposition with meteorological element data, had an improvement of 0.06 in the R2 of the model accuracy and a reduction of 2.93 and 1.14 in the root mean square error (RMSE) and mean absolute error (MAE), respectively, over the model using Aerosol Optical Depth (AOD). Our model had a prediction accuracy of R2 of 0.91, which was better than the other models. We used this model to estimate and analyze the variation in PM2.5 concentrations in the Beijing\u2013Tianjin\u2013Hebei region, and the results were the same as the actual PM2.5 concentration distribution trend. Obviously, the proposed model has a high prediction accuracy and can avoid the errors caused by the limitations of the AOD inversion method.<\/jats:p>","DOI":"10.3390\/rs14112714","type":"journal-article","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T00:10:33Z","timestamp":1654560633000},"page":"2714","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Estimation of Regional Ground-Level PM2.5 Concentrations Directly from Satellite Top-of-Atmosphere Reflectance Using A Hybrid Learning Model"],"prefix":"10.3390","volume":"14","author":[{"given":"Yu","family":"Feng","sequence":"first","affiliation":[{"name":"School of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0091-4182","authenticated-orcid":false,"given":"Shurui","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3968-481X","authenticated-orcid":false,"given":"Kewen","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China"}]},{"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Hebei University of Technology, Tianjin 300401, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1016\/j.jclepro.2019.04.231","article-title":"Estimating Ground-Level PM2.5 over a Coastal Region of China Using Satellite AOD and a Combined Model","volume":"227","author":"Yang","year":"2019","journal-title":"J. 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