The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Understanding land surface temperature impact factors based on local climate zones
Abstract
Abstract The local climate zone (LCZ) and land surface temperature (LST) have gained considerable attention as urbanization continues to increase. However, the study of LSTs lacks a regional complexity perspective. In order to explore the law of urban thermal environment, impact factors of LSTs are identified using GIS spatial analysis and statistical analysis methods in conjunction with parameter models that reflect urban spatial morphologies on the LCZ scale. The research results show that the LST ranges from 24.90 °C (LCZA) to 33.26 °C (LCZ2) in the summer of 2017 and from 2.53 °C (LCZ7) to 2.89 °C (LCZ3) in winter; LST ranged from 22.00 °C (LCZ2) to 28.19 °C (LCZE) in summer 2019, and from -4.79 °C (LCZ10) to -2.12 °C (LCZ3) in winter. Different LCZs had different impacts on LSTs. LST is always positively correlated with the floor area ratio, with a maximum correlation coefficient of 0.682 in LCZ2. It exhibits the highest positive correlation (correlation coefficient = 0.421) with average building height in LCZ3 and the highest negative correlation (correlation coefficient = -0.706) in LCZ7; vegetation and water bodies have a cooling effect. These results can serve as a valuable reference for building cool communities and improving the living environment of residents.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Local Climate Zones for Urban Temperature Studies
Stewart, I. D., & Oke, T. R. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00019.1 · Cited by 4,419
City size and the urban heat island
Oke, T. R. (1973) · Atmospheric Environment (1967) · doi:10.1016/0004-6981(73)90140-6 · Cited by 2,535
Estoque, R. C., Murayama, Y., & Myint, S. W. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2016.10.195 · Cited by 1,244
Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities
Bechtel, B., Alexander, P., Böhner, J., Ching, J., Conrad, O., Feddema, J., Mills, G., See, L., & Stewart, I. (2015) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi4010199 · Cited by 709
Evaluation of the ‘local climate zone’ scheme using temperature observations and model simulations
Stewart, I. D., Oke, T. R., & Krayenhoff, E. S. (2013) · International Journal of Climatology · doi:10.1002/joc.3746 · Cited by 594
Effects of the spatial configuration of trees on urban heat mitigation: A comparative study
Zhou, W., Wang, J., & Cadenasso, M. L. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.03.043 · Cited by 534
Amiri, R., Weng, Q., Alimohammadi, A., & Alavipanah, S. K. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2009.07.021 · Cited by 465
Effects of urban form on the urban heat island effect based on spatial regression model
Yin, C., Yuan, M., Lu, Y., Huang, Y., & Liu, Y. (2018) · Science of The Total Environment · doi:10.1016/j.scitotenv.2018.03.350 · Cited by 446
He, B.-J., Wang, J., Liu, H., & Ulpiani, G. (2021) · Environmental Research · doi:10.1016/j.envres.2020.110584 · Cited by 419
Influences of urban spatial form on urban heat island effects at the community level in China
Guo, A., Yang, J., Xiao, X., Xia (Cecilia), J., Jin, C., & Li, X. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2019.101972 · Cited by 371
Self-citation
Cited by
Xu, C., Wei, R., & Tong, H. (2025) · Sustainability · doi:10.3390/su17083747 · Cited by 18
Metadata
- Authors
- Yang, J., Ren, J., Sun, D., Xiao, X., Xia, J. (., Jin, C., & Li, X.
- Venue
- Sustainable Cities and Society
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 69
- Pages
- 102818
- ISSN
- 2210-6707 (ISSN-L)
- OpenAlex
- W3135821627
- Cited by
- 316
- References
- 54
- FWCI
- 17.08
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Understanding land surface temperature impact factors based on local climate zones. https://app.cochat.ai/papers/10.1016/j.scs.2021.102818
- The paper
- Yang, J., Ren, J., Sun, D., Xiao, X., Xia, J. (., Jin, C., & Li, X. (2021). Understanding land surface temperature impact factors based on local climate zones. Sustainable Cities and Society. https://doi.org/10.1016/j.scs.2021.102818
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.