Refined Mapping of Urban Local Climate Zones by Integrating Multi-source Data： A Case Study of Wuhan， China

LIU Yaolin; ZHANG Wen; JIAO Limin; QIN Rui; ZHANG Min

doi:10.13203/j.whugis20260214

您当前的位置：

首页 >

文章列表页 >

Refined Mapping of Urban Local Climate Zones by Integrating Multi-source Data： A Case Study of Wuhan， China

Cartography and GIS | 更新时间：2026-11-05

- Refined Mapping of Urban Local Climate Zones by Integrating Multi-source Data： A Case Study of Wuhan， China
- Geomatics and Information Science of Wuhan University Vol. 51, Issue 8, Pages: 1671-1684(2026)
- 作者机构：
  
  1.武汉大学资源与环境科学学院，湖北武汉，430079
  2.武汉大学地理信息系统教育部重点实验室，湖北武汉，430079
  3.昆山杜克大学，江苏昆山，215316
  4.武汉市自然资源和规划信息中心，湖北武汉，430014
- 作者简介：
- 基金信息：
- DOI：10.13203/j.whugis20260214
  CLC： P27
- Received：11 June 2026，
  
  Published：05 August 2026
- 稿件说明：
移动端阅览
刘耀林,张文,焦利民，等.融合多源数据的城市局地气候区精细分类方法研究——以武汉市为例[J].武汉大学学报（信息科学版）,2026,51(8):1671-1684.

LIU Yaolin,ZHANG Wen,JIAO Limin,et al.Refined Mapping of Urban Local Climate Zones by Integrating Multi-source Data: A Case Study of Wuhan, China[J].Geomatics and Information Science of Wuhan University,2026,51(8):1671-1684.
刘耀林,张文,焦利民，等.融合多源数据的城市局地气候区精细分类方法研究——以武汉市为例[J].武汉大学学报（信息科学版）,2026,51(8):1671-1684. DOI：10.13203/j.whugis20260214

LIU Yaolin,ZHANG Wen,JIAO Limin,et al.Refined Mapping of Urban Local Climate Zones by Integrating Multi-source Data: A Case Study of Wuhan, China[J].Geomatics and Information Science of Wuhan University,2026,51(8):1671-1684. DOI：10.13203/j.whugis20260214

摘要

在气候变化加剧和极端高温事件频发背景下，城市热环境评估、气候适应性规划和风险识别对精细化空间分类框架提出了更高要求。局地气候区（local climate zone

LCZ）分类作为连接城市空间形态与局地气候差异的基础框架，是气候变化背景下城市环境研究的重要支撑，但在复杂城市环境中仍存在类别混淆、分类精度不足等瓶颈问题。以湖北省武汉市为研究区，融合多源地理空间数据，提取建筑三维形态、地表覆盖、植被状态、光谱响应和功能约束等特征，构建知识规则—机器学习相结合的两阶段LCZ分类方法。基于独立人工解译样本的验证结果表明，120 m分辨率LCZ分类结果总体精度为0.899，Kappa系数为0.867；与相同验证样本下的全球LCZ产品相比，所构建方法结果的总体精度提高了0.130，Kappa系数提高了0.186。多尺度对比表明，120 m分类尺度在精度与空间细节表达之间具有相对均衡的表现。基于地表温度的外部一致性检验表明，分类结果能够有效反映不同城市形态与地表覆盖单元的热环境差异，表明该方法具有较好的城市局部气候特征区分性。所构建的集成方法可为复杂城市空间LCZ高精度分类、热环境精细化评估与气候适应性规划提供技术支撑。

Abstract

Objectives

Under intensifying climate change and increasingly frequent extreme heat events

urban thermal environment assessment

climate adaptation planning

and risk identification require more refined spatial classification frameworks. Local climate zone (LCZ) classification links urban spatial morphology with local climatic differences and provides an important basis for urban environmental research. However

LCZ classification in complex urban environments still faces bottlenecks such as class confusion and insufficient accuracy. The objective was to develop a refined LCZ classification method suitable for complex urban spaces and evaluate its local applicability.

Methods

With Wuhan as the study area

multi-source geospatial data for 2020 were integrated to construct features related to three-dimensional building morphology

surface cover

vegetation conditions

spectral responses

and functional constraints. A two-stage LCZ classification method was formed by combining knowledge-rule-based initial classification with random forest supplementary classification. Classification accuracy

multi-scale performance

comparison with the global LCZ product

and land-surface-temperature-based external consistency were evaluated.

Results

The 120 m LCZ classification result achieved an overall accuracy (OA) of 0.899

with an overall accuracy of 0.827 for built-up LCZ classes. Compared with the global LCZ product evaluated using the same validation samples

the OA and Kappa coefficient of the proposed result were higher by 0.130 and 0.186

respectively. Multi-scale comparison showed that the 120 m classification scale achieved a relatively balanced performance between accuracy and spatial detail representation. The land surface temperature consistency test showed that the classification result effectively reflected thermal differences among urban morphology and surface-cover units

supporting the climatic interpretability and applicability of the LCZ classification method.

Conclusions

The results can provide technical support for high-accuracy LCZ classification

refined urban thermal environment assessment

and climate adaptation planning in complex urban spaces.

关键词

Keywords

references

LIU X P ， WU X X ， LI X C ， et al . Global Mapping of Three-Dimensional Urban Structures Reveals Escalating Utilization in the Vertical Dimension and Pronounced Building Space Inequality ［J］. Engineering ， 2025 ， 47 ： 86 - 99 .

ROCHA A D ， VULOVA S ， FÖRSTER M ， et al . Unprivileged Groups Are less Served by Green Cooling Services in Major European Urban Areas ［J］. Nature Cities ， 2024 ， 1 （ 6 ）： 424 - 435 .

WANG X ， ZHOU L ， SONG Y Z ， et al . Beyond Flat Cities： Dramatic 2D/3D Differences in Urban Gray-Green Space Configurations and the Nonlinear Thermal Regulation Mechanisms ［J］. GIScience & Remote Sensing ， 2025 ， 62 （ 1 ）： 2572174 .

WANG R F ， WANG M M ， REN C ， et al . Mapping Local Climate Zones and Its Applications at the Global Scale： A Systematic Review of the Last Decade of Progress and Trend ［J］. Urban Climate ， 2024 ， 57 ： 102129 .

ZHAO J Y ， YU L . Application of LCZ to Time-Series Urban Morphology Detection ［M］// Local Climate Zone Application in Sustainable Urban Development： Experience from East and Southeast Asian High-Density Cities . Cham ： Springer ， 2024 ： 191 - 203 .

ACOSTA-FERNÁNDEZ G A ， MARTÍNEZ-TORRES K E ， GONZÁLEZ-TREVIZO M E ， et al . Advances in Urban Mapping of Local Climate Zones for Heat Mitigation： A Systematic Review ［J］. Land Use Policy ， 2025 ， 153 ： 107540 .

LIN Z L ， XU H Q ， HU X S ， et al . Characterizing the Seasonal Relationships Between Urban Heat Island and Surface Energy Balance Fluxes Considering the Impact of Three-Dimensional Urban Morphology ［J］. Building and Environment ， 2024 ， 265 ： 112017 .

STEWART I D ， OKE T R . Local Climate Zones for Urban Temperature Studies ［J］. Bulletin of the American Meteorological Society ， 2012 ， 93 （ 12 ）： 1879 - 1900 .

杨俊，辛佳兴，任嘉义，等 . 局地气候分区与人口密度的复合作用对城市热岛效应的影响［J］. 地理学报， 2025 ， 80 （ 5 ）： 1370 - 1385 .

YANG Jun ， XIN Jiaxing ， REN Jiayi ， et al . Dual Drivers of the Urban Heat Island Effect： The Compound Effect of Local Climate Zones and Population Density ［J］. Acta Geographica Sinica ， 2025 ， 80 （ 5 ）： 1370 - 1385 .

DENG H J ， FENG J L ， LIU K ， et al . Local Climate Zone Framework： Seasonal Dynamics of Surface Urban Heat Island and Its Influencing Factors in Three Chinese Urban Agglomerations ［J］. GIScience & Remote Sensing ， 2025 ， 62 （ 1 ）： 2490317 .

CHEN H J ， YOO C ， LO J T Y . A 3-Dimension Urban Growth Analysis Using Local Climate Zone Mapping ［J］. GIScience & Remote Sensing ， 2025 ， 62 （ 1 ）： 2473158 .

HU J ， ZHOU Y Y ， YANG Y B ， et al . Multi-City Local Climate Zone Mapping and Its Quantitative Applications on Measuring Surface Urban Heat Island in China ［J］. Remote Sensing of Environment ， 2025 ， 330 ： 114965 .

LIU S J ， SHI Q . Local Climate Zone Mapping as Remote Sensing Scene Classification Using Deep Learning： A Case Study of Metropolitan China ［J］. ISPRS Journal of Photogrammetry and Remote Sensing ， 2020 ， 164 ： 229 - 242 .

ZHU Q Q ， RAN L L ， ZHANG Y C ， et al . Integrating Geographic Knowledge into Deep Learning for Spatiotemporal Local Climate Zone Mapping Derived Thermal Environment Exploration Across Chinese Climate Zones ［J］. ISPRS Journal of Photogrammetry and Remote Sensing ， 2024 ， 217 ： 53 - 75 .

BECHTEL B ， ALEXANDER P ， BÖHNER J ， et al . Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities ［J］. ISPRS International Journal of Geo-Information ， 2015 ， 4 （ 1 ）： 199 - 219 .

CHING J ， MILLS G ， BECHTEL B ， et al . WUDAPT： An Urban Weather， Climate， and Environmental Modeling Infrastructure for the Anthropocene ［J］. Bulletin of the American Meteorological Society ， 2018 ， 99 （ 9 ）： 1907 - 1924 .

DEMUZERE M ， KITTNER J ， MARTILLI A ， et al . A Global Map of Local Climate Zones to Support Earth System Modelling and Urban-Scale Environmental Science ［J］. Earth System Science Data ， 2022 ， 14 （ 8 ）： 3835 - 3873 .

REN C ， CAI M ， LI X W ， et al . Assessment of Local Climate Zone Classification Maps of Cities in China and Feasible Refinements ［J］. Scientific Reports ， 2019 ， 9 ： 18848 .

YU H G ， YANG Y ， ZHAO J Y ， et al . Dynamic Urban Morphology Mapping in Chinese Cities Based on Local Climate Zone Approach ［J］. Scientific Data ， 2025 ， 12 ： 181 .

SHI L F ， LING F . Local Climate Zone Mapping Using Multi-source Free Available Datasets on Google Earth Engine Platform ［J］. Land ， 2021 ， 10 （ 5 ）： 454 .

ZHONG J ， LIU J F ， JIAO L M ， et al . Assessing the Comprehensive Impacts of Different Urbanization Process on Vegetation Net Primary Productivity in Wuhan， China， from 1990 to 2020 ［J］. Sustainable Cities and Society ， 2021 ， 75 ： 103295 .

HUANG X ， WANG Y . Investigating the Effects of 3D Urban Morphology on the Surface Urban Heat Island Effect in Urban Functional Zones by Using High-Resolution Remote Sensing Data： A Case Study of Wuhan， Central China ［J］. ISPRS Journal of Photogrammetry and Remote Sensing ， 2019 ， 152 ： 119 - 131 .

ZHANG M M ， KAFY A A ， XIAO P N ， et al . Impact of Urban Expansion on Land Surface Temperature and Carbon Emissions Using Machine Learning Algorithms in Wuhan， China ［J］. Urban Climate ， 2023 ， 47 ： 101347 .

CHE Y Z ， LI X C ， LIU X P ， et al . 3D-GloBFP： The First Global Three-Dimensional Building Footprint Dataset ［J］. Earth System Science Data ， 2024 ， 16 （ 11 ）： 5357 - 5374 .

KARRA K ， KONTGIS C ， STATMAN-WEIL Z ， et al . Global Land Use / Land Cover with Sentinel 2 and Deep Learning ［C］// IEEE International Geoscience and Remote Sensing Symposium IGARSS ， Brussels， Belgium ， 2021 .

GEOLOGICAL SURVEY U S . Landsat Collection 2 Level-2 Science Products： Fact Sheet 2021-3055： 2021-3055 ［R］. Reston， VA ： U.S. Geological Survey ， 2021 .

GONG P ， LI X C ， WANG J ， et al . Annual Maps of Global Artificial Impervious Area （GAIA） Between 1985 and 2018 ［J］. Remote Sensing of Environment ， 2020 ， 236 ： 111510 .

CAI Y T ， XU X C ， ZHU P ， et al . Unveiling Spatiotemporal Tree Cover Patterns in China： The First 30 m Annual Tree Cover Mapping from 1985 to 2023 ［J］. ISPRS Journal of Photogrammetry and Remote Sensing ， 2024 ， 216 ： 240 - 258 .

XIONG S ， ZHANG X ， DU S ， et al . 40 -Year （ 1984 — 2024 ） Record of Urban Land Use Dynamic Changes of China ［EB/OL］. （ 2026-03-16 ）［ 2026-05-25 ］. https：//zenodo.org/records/19042096 https://zenodo.org/records/19042096 .

HU J ， YANG Y B ， PAN X ， et al . Analysis of the Spatial and Temporal Variations of Land Surface Temperature Based on Local Climate Zones： A Case Study in Nanjing， China ［J］. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ， 2019 ， 12 （ 11 ）： 4213 - 4223 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Negative Sample Selection and Result Optimization for Landslide Susceptibility Assessment Considering InSAR Surface Deformation

Identification of Debris-Covered Koxkar Glacier in Mt. Tianshan and Its Velocity Characteristics

Classification of Vegetation Information by Integrating Color Features with Multi-feature Optimization of Random Forest in the Yellow River Delta

Spatiotemporal Evolution of Disaster and Population Casualties in Jishishan Earthquake by Fusing Multi-source Data

An Oasis Soil Moisture Inversion Model Using ALOS-2 and Landsat 8 Data

Related Author

FAN Luzhen

HE Guoqing

SHAN Yunfeng

ZHOU Shengsen

LI Weile

QIN Jiasong

HAN Hui

HAN Haidong

Related Institution

Laboratory of Landslide Risk Early‑Warning and Control, Ministry of Emergency Management

State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology

Gansu Provincial Engineering Laboratory for National Geographic State Monitoring

Nation⁃Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring

University of Chinese Academy of Sciences

AI问答

⁰