关键词: 局地气候区, 城市热环境, 地表温度, 城市形态, 空间误差模型, 澳门

Abstract: It is crucial to understand the relationship between the complicated spatial morphology of cities and their thermal environment to deal with the increasing risks of high-temperature heat waves. Hence, a case study based on Macao was conducted. First, the optimal partition scale (120 m × 120 m) of local climate zones (LCZs) was determined using the semi-variogram function and Pearson correlation coefficient. The LCZs in Macao were delineated by remote sensing interpretation in ENVI, GIS spatial analysis, CART decision tree classification, and other methods. Second, surface temperature data in Macao were collected using remote sensing image inversion techniques. Eight urban morphological indicators with significant correlations with the thermal environment, namely sky view factor (SVF), building density (BD), building volume density (BVD), building height (BH), building height variation (BH_S), impervious surface density (ISD), green space density (GSD), and water surface density (WSD), were acquired via the ArcGIS data analysis technique as independent variables. Later, the correlations between independent and dependent variables were analyzed quantitatively through a spatial error model (SEM) with the best fitting effect, thus disclosing the key influencing factors and mechanisms of thermal environments in different subzones of LCZs. Finally, the thermal environment optimization level of each subzone of LCZs was evaluated comprehensively from "Optimization Necessity (ON), Optimization Effectiveness (OE), Strategy Effectiveness (SE), and Strategy Feasibility (SF)". Optimization suggestions were then proposed based on the evaluation results. The results demonstrated that: 1) The northern regions of the Macao Peninsula are dominated by LCZ2 (compact mid-rise), LCZ4 (open high-rise), and LCZ5 (open mid-rise), with a small number of green space-type LCZs (LCZA~D). The southern regions of Taipa, Coloane, and Cotai have more blue-green spaces, and open-formed LCZs dominate built-type LCZs. 2) LCZs dominated by medium-low-rise buildings (LCZ6~10) and bare ground (LCZE~F) exhibit significant warming effects, whereas LCZs dominated by trees (LCZA~B), water bodies (LCZG), and high-rise buildings (LCZ1, LCZ4) exhibit significant cooling effects. The cooling effect of shrubs and low vegetation (LCZC~D) is less prominent. For built-up LCZs, blocking solar radiation is more favorable for cooling than ventilation and heat dissipation approaches. 3) The SEM better describes the relationship between urban morphology and the thermal environment in Macao. However, it also demonstrated that other variables or independent error terms might affect the surface temperature, which shall be further analyzed and discussed in future studies. 4) The key influencing factors and their coefficients vary significantly among different subzones of LCZs, indicating that adaptive thermal environment optimization strategies shall be selected for different subzones of LCZs. 5) SVF, BD, BVD, and ISD exhibit warming effects, whereas BH, BH_S, GSD, and WSD present cooling effects. Influencing coefficients of GSD, WSD, ISD, and BVD are generally high. 6) Macao is recommended to first optimize the thermal environment in LCZ10 (heavy industry), LCZF (bare soil or sand), LCZ4 (open high-rise), LCZ5 (open mid-rise), LCZA (dense trees), and LCZ6 (open low-rise). In addition, crucial influencing factors shall be determined by combining SEM for differentiated planning and design of spatial elements in each subzone. This study supports formulating countermeasures to high-temperature risks in high-density cities like Macao.

Key words: local climate zones, urban thermal environment, land surface temperature, urban morphology, spatial error model, Macao