太阳成8722(中国)有限公司-GREEN NO.1

标题: Generating Comparable and Fine-Scale Time Series of Summer Land Surface Temperature for Thermal Environment Monitoring

作者: Shen, Y (Shen, Yao); Shen, HF (Shen, Huanfeng); Cheng, Q (Cheng, Qing); Zhang, LP (Zhang, Liangpei)

来源出版物: IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING  卷: 14  页: 2136-2147  DOI: 10.1109/JSTARS.2020.3046755  出版年: 2021  

摘要: Satellite images have been widely used for urban heat island (UHI) monitoring in recent studies, among which the summer UHI has attracted more attention. However, the studies based on high spatial resolution images have to use single-day land surface temperature (LST) to analyze the summer UHI, due to the low temporal resolution, which is not representative of the summer and leads to incomparability in the time series. The studies based on low spatial resolution images can generate a time series of representative LSTs for summer (e.g., summer mean LSTs), due to the high temporal resolution, but these LSTs lack sufficient spatial details for a refined analysis. To fill these gaps, we propose to integrate the respective advantages of the above approaches to generate a comparable and fine-scale LST time series with a high spatiotemporal resolution. By normalizing the LSTs between the different satellite images via robust fitting with Huber's M-estimator and moment matching, the comparability is ensured. Furthermore, the high-spatial resolution and high-temporal resolution are combined via the spatiotemporal fusion. Overall, we propose a procedure to produce a comparable time series of annual and fine-scale summer mean LSTs, which can serve as a basis for elaborate analysis of the thermal environment.

入藏号: WOS:000616306700001

语言: English

文献类型: Article

作者关键词: Spatial resolution; Land surface temperature; Remote sensing; Earth; Artificial satellites; Spatiotemporal phenomena; Time series analysis; Land surface temperature (LST) normalization; remote sensing; spatiotemporal fusion; summer mean LST (SMLST)

地址: [Shen, Yao; Shen, Huanfeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

[Shen, Huanfeng] Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430072, Peoples R China.

[Cheng, Qing] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China.

[Zhang, Liangpei] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping and, Wuhan 430072, Peoples R China.

通讯作者地址: Shen, HF (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

Shen, HF (通讯作者)，Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan 430072, Peoples R China.

电子邮件地址: shenyao_sy@whu.edu.cn; shenhf@whu.edu.cn; qingcheng@whu.edu.cn; zlp62@whu.edu.cn

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