國家衛生研究院 NHRI:Item 3990099045/12773

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Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/12773

Title:	New land use regression model to estimate atmospheric temperature and heat island intensity in Taiwan
Authors:	Hsu, CY;Ng, UC;Chen, CY;Chen, YC;Chen, MJ;Chen, NT;Lung, SCC;Su, HJ;Wu, CD
Contributors:	National Institute of Environmental Health Sciences
Abstract:	This paper is about spatial–temporal variability of atmospheric temperature across Taiwan, an island with diverse local emission sources partly because of its Asian cultural characteristics. To develop a new land use regression (LUR) model for this study, we used the temperature data collected by the Taiwan Central Weather Bureau from 2000 and 2016, while using the data from 2017 as the external data verification to assess model reliability. Because incense and joss money burning is a cultural-specific emission source in Asia, we further included location of temples, cemeteries, and crematoriums as potential predictors. The overall model performance and tenfold cross-validated are R2 of 0.88 and R2 of 0.87, respectively, which presents a high level of prediction performance. Moreover, we used our LUR model to estimate urban heat islands intensity (UHII) for six metropolises in Taiwan and found Taichung City has the highest UHII value (4.60 °C) among them. These results provide important insights in expanding the remote sensing application on spatial–temporal variation of atmospheric temperature and its further application on UHI effects.
Date:	2020-08
Relation:	Theoretical and Applied Climatology. 2020 Aug;141:1451-1459.
Link to:	http://dx.doi.org/10.1007/s00704-020-03286-1
JIF/Ranking 2023:	http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0177-798X&DestApp=IC2JCR
Cited Times(WOS):	https://www.webofscience.com/wos/woscc/full-record/WOS:000539785100001
Cited Times(Scopus):	https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85086395588
Appears in Collections:	[Yu-Cheng Chen] Periodical Articles

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