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Correction: Schneider et al. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM 2.5 Concentrations across Great Britain. Remote Sens. 2020, 12 , 3803.

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Title: Correction: Schneider et al. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM 2.5 Concentrations across Great Britain. Remote Sens. 2020, 12 , 3803.
Authors: Schneider, Rochelle1,2,3 (AUTHOR) francesco.sera@lshtm.ac.uk, Vicedo-Cabrera, Ana M.4,5 (AUTHOR) ana.vicedo-cabrera@lshtm.ac.uk, Sera, Francesco1 (AUTHOR) pierre.masselot@lshtm.ac.uk, Masselot, Pierre1 (AUTHOR) Antonio.Gasparrini@lshtm.ac.uk, Stafoggia, Massimo6 (AUTHOR) m.stafoggia@deplazio.it, de Hoogh, Kees7,8 (AUTHOR) c.dehoogh@swisstph.ch, Kloog, Itai9 (AUTHOR) ikloog@bgu.ac.il, Reis, Stefan10,11 (AUTHOR) srei@ceh.ac.uk, Vieno, Massimo10 (AUTHOR) mvi@ceh.ac.uk, Gasparrini, Antonio1,2,12 (AUTHOR)
Source: Remote Sensing. Sep2021, Vol. 13 Issue 18, p3588. 1p.
Subjects: Machine learning
Geographic Terms: United Kingdom
Abstract: Reference 1 Schneider R., Vicedo-Cabrera A.M., Sera F., Masselot P., Stafoggia M., de Hoogh K., Kloog I., Reis S., Vieno M., Gasparrini A. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM2.5 Concentrations across Great Britain. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM 2.5 Concentrations across Great Britain. Figure Graph: Figure 3 Stage-4 predicted PM2.5 concentrations across Great Britain (Top) and London (Bottom) for 2008, 2013, and 2018 aggregated by annual means. [Extracted from the article]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Correction: Schneider et al. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM 2.5 Concentrations across Great Britain. Remote Sens. 2020, 12 , 3803.
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  Data: <searchLink fieldCode="AR" term="%22Schneider%2C+Rochelle%22">Schneider, Rochelle</searchLink><relatesTo>1,2,3</relatesTo> (AUTHOR)<i> francesco.sera@lshtm.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Vicedo-Cabrera%2C+Ana+M%2E%22">Vicedo-Cabrera, Ana M.</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<i> ana.vicedo-cabrera@lshtm.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Sera%2C+Francesco%22">Sera, Francesco</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> pierre.masselot@lshtm.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Masselot%2C+Pierre%22">Masselot, Pierre</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> Antonio.Gasparrini@lshtm.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Stafoggia%2C+Massimo%22">Stafoggia, Massimo</searchLink><relatesTo>6</relatesTo> (AUTHOR)<i> m.stafoggia@deplazio.it</i><br /><searchLink fieldCode="AR" term="%22de+Hoogh%2C+Kees%22">de Hoogh, Kees</searchLink><relatesTo>7,8</relatesTo> (AUTHOR)<i> c.dehoogh@swisstph.ch</i><br /><searchLink fieldCode="AR" term="%22Kloog%2C+Itai%22">Kloog, Itai</searchLink><relatesTo>9</relatesTo> (AUTHOR)<i> ikloog@bgu.ac.il</i><br /><searchLink fieldCode="AR" term="%22Reis%2C+Stefan%22">Reis, Stefan</searchLink><relatesTo>10,11</relatesTo> (AUTHOR)<i> srei@ceh.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Vieno%2C+Massimo%22">Vieno, Massimo</searchLink><relatesTo>10</relatesTo> (AUTHOR)<i> mvi@ceh.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Gasparrini%2C+Antonio%22">Gasparrini, Antonio</searchLink><relatesTo>1,2,12</relatesTo> (AUTHOR)
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  Data: Reference 1 Schneider R., Vicedo-Cabrera A.M., Sera F., Masselot P., Stafoggia M., de Hoogh K., Kloog I., Reis S., Vieno M., Gasparrini A. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM2.5 Concentrations across Great Britain. A Satellite-Based Spatio-Temporal Machine Learning Model to Reconstruct Daily PM 2.5 Concentrations across Great Britain. Figure Graph: Figure 3 Stage-4 predicted PM2.5 concentrations across Great Britain (Top) and London (Bottom) for 2008, 2013, and 2018 aggregated by annual means. [Extracted from the article]
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  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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