Analysis of surface urban heat islands based on local climate zones via spatiotemporally enhanced land surface temperature
文献类型：期刊论文
| 作者 | Xia, Haiping1,2,3; Chen, Yunhao2; Song, Conghe4; Li, Junxiang5; Quan, Jinling6; Zhou, Guomo1,3 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2022-05-01 |
| 卷号 | 273页码:21 |
| 关键词 | Spatial downscaling Temporal interpolation Surface urban heat islands Local climate zone |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2022.112972 |
| 通讯作者 | Chen, Yunhao(cyh@bnu.edu.cn) |
| 英文摘要 | Surface Urban heat island (SUHI) is a major adverse environmental consequence of urbanization. Many algo-rithms measuring SUHI across varying spatial or temporal scales are developed rapidly with the availability of thermal infrared (TIR) remote sensing data from satellites. However, the trade-off between the spatial and temporal resolution of TIR sensors limits the study of SUHI on both spatial and temporal domains. Therefore, this study aims to improve the characterization of SUHI using spatiotemporally enhanced land surface temperature (LST) derived from the synergistic use of coarse-and fine-spatial-resolution TIR data. Combining the spatial downscaling and temporal interpolation techniques, we generated daily 100 m-resolution LST in both daytime and nighttime to analyze the SUHI in different local climate zones (LCZs) in Beijing. LCZ is a manifestation of the urban form on the thermal environment, covering hundreds of meters to several kilometers in horizontal scale. The results indicate the spatiotemporally enhanced LST is reliable in capturing the LCZ-based SUHI magnitude compared with original observations, and providing a more accurate time range when the SUHI reaches to its maximum compared with those time-discontinuous original observations. Compared with temporally interpo-lated coarse-resolution LST, the spatiotemporally enhanced LST shows a larger annual variation of SUHI (especially in LCZ 2 with a mean absolute SUHI difference of 0.8 K and 1.3 K for daytime and nighttime, respectively) and provides larger SUHI difference between compact building and open building (especially when there is a significant SUHI effect). The superiority of the spatiotemporally enhanced LSTs in analyzing LCZ-based SUHI is more evident in daily and monthly SUHI analysis than in single-day analysis or annual analysis, espe-cially in compact building types (LCZ 1 and 2). These findings are valuable information for better and healthier urban planning for SUHI mitigation and public health care. |
| WOS关键词 | TEMPORAL TRENDS ; TIME-SERIES ; SATELLITE ; AREA ; INDICATORS ; RETRIEVAL ; ALGORITHM ; PATTERNS ; PRODUCT ; FUSION |
| 资助项目 | Beijing Natural Science Foundation[8192025] ; Projects of Beijing Advanced Innovation Center for Future Urban Design, Beijing University of Civil Engineering and Architecture[UDC2019031321] ; Beijing Laboratory of Water Resources Security |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000767960300001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 资助机构 | Beijing Natural Science Foundation ; Projects of Beijing Advanced Innovation Center for Future Urban Design, Beijing University of Civil Engineering and Architecture ; Beijing Laboratory of Water Resources Security |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/172696]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Chen, Yunhao |
| 作者单位 | 1.Zhejiang A&F Univ, State Key Lab Subtrop Silviculture, Hangzhou 311300, Peoples R China 2.Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China 3.Zhejiang A&F Univ, Sch Environm & Resources Sci, Hangzhou 311300, Peoples R China 4.Univ N Carolina, Dept Geog, Chapel Hill, NC 27599 USA 5.Shanghai Jiao Tong Univ, Sch Design, Dept Landscape Architecture, Shanghai 200240, Peoples R China 6.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xia, Haiping,Chen, Yunhao,Song, Conghe,et al. Analysis of surface urban heat islands based on local climate zones via spatiotemporally enhanced land surface temperature[J]. REMOTE SENSING OF ENVIRONMENT,2022,273:21. |
| APA | Xia, Haiping,Chen, Yunhao,Song, Conghe,Li, Junxiang,Quan, Jinling,&Zhou, Guomo.(2022).Analysis of surface urban heat islands based on local climate zones via spatiotemporally enhanced land surface temperature.REMOTE SENSING OF ENVIRONMENT,273,21. |
| MLA | Xia, Haiping,et al."Analysis of surface urban heat islands based on local climate zones via spatiotemporally enhanced land surface temperature".REMOTE SENSING OF ENVIRONMENT 273(2022):21. |
入库方式： OAI收割
来源：地理科学与资源研究所
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