Urban Heat Island Mitigation Open access Peer reviewed

Characterizing the Mismatch Between ECOSTRESS-Derived Land Surface Temperature and ENVI-Met-Simulated UTCI Across Local Climate Zones

Jiancheng Ai, Yuhan Zhang, Zhe Li

Remote Sensing | Aug 12, 2026

Abstract

Abstract

Satellite-derived land surface temperature (LST) is widely used for urban heat assessment, but its correspondence with pedestrian exposure is uncertain. We compared ECOSTRESS-derived LST with ENVI-met-simulated Universal Thermal Climate Index (UTCI), treated as a model-based heat-exposure indicator, across 24 Seoul Local Climate Zone plots. One ECOSTRESS scene acquired five days before the ENVI-met simulation served as the primary near-date, hour-matched comparison under comparable meteorological conditions rather than a simultaneous field observation; four scenes from 2021–2025 were treated as separate cross-date sensitivity observations. A source audit retained 118 of 120 plot × scene records. The primary association was weak (r = 0.199, p = 0.351, R2 = 0.040, n = 24). The unadjusted pooled benchmark explained 6.1% of UTCI variance, whereas the scene-adjusted LST slope was 0.060 °C UTCI per °C LST (plot-cluster-robust 95% CI −0.075 to 0.195; p = 0.371). Because only two plots represented each LCZ, leave-one-plot-out and stratified bootstrap results were interpreted only as discrete perturbation diagnostics. ECOSTRESS LST therefore did not demonstrate stable proxy performance for simulated pedestrian heat exposure under this design. CPE is retained as a conceptual organizing heuristic, not a validated classifier or transferable LCZ ranking.

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Authors

Researchers on this paper

Jiancheng Ai

first | Edinburgh College | ORCID 0009-0008-1017-3534

Yuhan Zhang

middle | Seoul National University | ORCID 0000-0003-1225-0990

Zhe Li

last | Southeast University | ORCID 0000-0003-2382-4611

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Citation

BibTeX

@article{Ai2026Characterizing,
  title = {Characterizing the Mismatch Between ECOSTRESS-Derived Land Surface Temperature and ENVI-Met-Simulated UTCI Across Local Climate Zones},
  author = {Jiancheng Ai and Yuhan Zhang and Zhe Li},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18162712},
  url = {https://doi.org/10.3390/rs18162712}
}

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