Ground-based remote sensing and machine learning for in situ and noninvasive monitoring and identification of salts and moisture in historic buildings

Kogou, S ORCID: https://orcid.org/0000-0003-1722-7626, Li, Y, Cheung, CS, Han, XN, Liggins, F, Shahtahmassebi, G ORCID: https://orcid.org/0000-0002-0630-2750, Thickett, D and Liang, H ORCID: https://orcid.org/0000-0001-9496-406X, 2025. Ground-based remote sensing and machine learning for in situ and noninvasive monitoring and identification of salts and moisture in historic buildings. Analytical Chemistry, 97 (9), pp. 5008-5013. ISSN 0003-2700

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Item Type:	Journal article
Publication Title:	Analytical Chemistry
Creators:	Kogou, S., Li, Y., Cheung, C.S., Han, X.N., Liggins, F., Shahtahmassebi, G., Thickett, D. and Liang, H.
Publisher:	American Chemical Society (ACS)
Date:	11 March 2025
Volume:	97
Number:	9
ISSN:	0003-2700
Identifiers:	Number Type 10.1021/acs.analchem.4c05581 DOI 2412416 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Borcherds
Date Added:	24 Mar 2025 10:19
Last Modified:	24 Mar 2025 10:19
URI:	https://irep.ntu.ac.uk/id/eprint/53284

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