Urban areas are hot spots that drive environmental change at multiple scales. Material demands of production and human consumption alter land use and cover, biodiversity, and hydrosystems locally to regionally, and urban waste discharge affects local to global biogeochemical cycles and climate. For urbanites, however, global environmental changes are swamped by dramatic changes in the local environment. Urban ecology integrates natural and social sciences to study these radically altered local environments and their regional and global effects. Cities themselves present both the problems and solutions to sustainability challenges of an increasingly urbanized world.

随着全球城市化的快速发展和气候变暖及极端高温事件的加剧，城市热岛效应已成为了21世纪影响人类生存发展的重要环境问题。因此，阐明城市热岛强度时空变化特征，揭示多空间尺度下的形成机制是人文地理学和气候学研究的热点和前沿交叉科学问题。从街道峡谷微观尺度、城市街区局部尺度和城市宏观尺度全面总结和系统梳理了城市空间形态对城市热岛效应的多尺度影响和耦合机制，提出了未来通过定量表征城市热岛强度、城市空间形态的空间格局、时间演化特征及规律，构建空间关系分析模型，进而揭示城市空间形态在不同时空尺度对城市热岛强度的作用机制，为城市规划、宜居城市建设以及气候变化的响应与适应研究提供理论指导。

With the rapid development of global urbanization, the further increased global warming and extreme high temperature events, urban heat island effect has also become an important environmental problem affecting human survival and development in the 21st century. Therefore, it is a hot and frontier cross-scientific issue in the study of human geography and climatology to clarify the spatio-temporal variations of urban heat island intensity and reveal the driving mechanism at multi-spatial scales. Urban geometry is regarded as a key factor affecting urban-rural and intra-urban air temperature variations, and the urban form manipulation provides an opportunity to mitigate the adverse effects on urban climate. Therefore, it is critical to understand the relationship between urban form and the UHI effect to guide future planning practice. This paper systematically reviews and summarizes the multi-scale affecting and coupling mechanism of urban spatial morphology on urban heat island intensity from three different spatial scale perspectives including street canyons microscale, urban block local scale, and urban macroscale. Based on the understanding of the spatial distribution and temporal evolution characteristics of urban spatial morphology on urban heat island intensity, we will characterize the specific effects of urban spatial morphology on urban heat island intensity and construct the spatial relationship analysis model to reveal the affecting mechanism of urban spatial morphology on urban heat island intensity at different temporal and spatial scales. Our knowledge and insights will provide theoretical guidance for urban planning, livable city construction and climate change response and adaptation study.

Urban Heat Island (UHI) is considered as one of the major problems in the 21st century posed to human beings as a result of urbanization and industrialization of human civilization. The large amount of heat generated from urban structures, as they consume and re-radiate solar radiations, and from the anthropogenic heat sources are the main causes of UHI. The two heat sources increase the temperatures of an urban area as compared to its surroundings, which is known as Urban Heat Island Intensity (UHII). The problem is even worse in cities or metropolises with large population and extensive economic activities. The estimated three billion people living in the urban areas in the world are directly exposed to the problem, which will be increased significantly in the near future. Due to the severity of the problem, vast research effort has been dedicated and a wide range of literature is available for the subject. The literature available in this area includes the latest research approaches, concepts, methodologies, latest investigation tools and mitigation measures. This study was carried out to review and summarize this research area through an investigation of the most important feature of UHI. It was concluded that the heat re-radiated by the urban structures plays the most important role which should be investigated in details to study urban heating especially the UHI. It was also concluded that the future research should be focused on design and planning parameters for reducing the effects of urban heat island and ultimately living in a better environment.

The effect of urban development on local thermal climate is widely documented in scientific literature. Observations of urban–rural air temperature differences—or urban heat islands (UHIs)—have been reported for cities and regions worldwide, often with local field sites that are extremely diverse in their physical and climatological characteristics. These sites are usually described only as “urban” or “rural,” leaving much uncertainty about the actual exposure and land cover of the sites. To address the inadequacies of urban–rural description, the “local climate zone” (LCZ) classification system has been developed. The LCZ system comprises 17 zone types at the local scale (102 to 104 m). Each type is unique in its combination of surface structure, cover, and human activity. Classification of sites into appropriate LCZs requires basic metadata and surface characterization. The zone definitions provide a standard framework for reporting and comparing field sites and their temperature observations. The LCZ system is designed primarily for urban heat island researchers, but it has derivative uses for city planners, landscape ecologists, and global climate change investigators.

Urban areas globally are vulnerable to warming climate trends exacerbated by their growing populations and heat island effects. The Local Climate Zone (LCZ) typology has become a popular framework for characterizing urban microclimates in different regions using various classification methods, including a widely adopted pixel-based protocol by the World Urban Database and Access Portal Tools (WUDAPT) Project. However, few studies to date have explored the potential of object-based image analysis (OBIA) to facilitate classification of LCZs given their inherent complexity, and few studies have further used the LCZ framework to analyze land cover changes in urban areas over time. This study classified LCZs in the Salt Lake Metro Region, Utah, USA for 1993 and 2017 using a supervised object-based analysis of Landsat satellite imagery and assessed their change during this time frame. The overall accuracy, measured for the most recent classification period (2017), was equal to 64% across 12 LCZs, with most of the error resulting from similarities among highly developed LCZs and non-developed classes with sparse or low-stature vegetation. The observed 1993–2017 changes in LCZs indicated a regional tendency towards primarily suburban, open low-rise development, and large low-rise and paved classes. However, despite the potential for local cooling with landscape transitions likely to increase vegetation cover and irrigation compared to pre-development conditions, summer averages of Landsat-derived top-of-atmosphere brightness temperatures showed a pronounced warming between 1992–1994 and 2016–2018 across the study region, with a 0.1–2.9 °C increase among individual LCZs. Our results indicate that future applications of LCZs towards urban change analyses should develop a stronger understanding of LCZ microclimate sensitivity to changes in size and configuration of urban neighborhoods and regions. Furthermore, while OBIA is promising for capturing the heterogeneous and multi-scale nature of LCZs, its applications could be strengthened by adopting more generalizable approaches for LCZ-relevant segmentation and validation, and by incorporating active remote sensing data to account for the 3D complexity of urban areas.

Diurnal cycling of plant carbon uptake and water use, and their responses to water and heat stresses, provide direct insight into assessing ecosystem productivity, agricultural production and management practices, carbon and water cycles, and feedbacks to the climate. Temperature, light, atmospheric water demand, soil moisture and leaf water potential vary over the course of the day, leading to diurnal variations in stomatal conductance, photosynthesis and transpiration. Earth observations from polar-orbiting satellites are incapable of studying these diurnal variations. Here, we review the emerging satellite observations that have the potential for studying how plant functioning and ecosystem processes vary over the course of the diurnal cycle. The recently launched ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Orbiting Carbon Observatory-3 (OCO-3) provide land surface temperature, evapotranspiration (ET), gross primary production (GPP) and solar-induced chlorophyll fluorescence data at different times of day. New generation operational geostationary satellites such as Himawari-8 and the GOES-R series can provide continuous, high-frequency data of land surface temperature, solar radiation, GPP and ET. Future satellite missions such as GeoCarb, TEMPO and Sentinel-4 are also planned to have diurnal sampling capability of solar-induced chlorophyll fluorescence. We explore the unprecedented opportunities for characterizing and understanding how GPP, ET and water use efficiency vary over the course of the day in response to temperature and water stresses, and management practices. We also envision that these emerging observations will revolutionize studies of plant functioning and ecosystem processes in the context of climate change and that these observations and findings can inform agricultural and forest management and lead to improvements in Earth system models and climate projections.

Rapid 21st century urbanization combined with anthropogenic climate warming are significantly increasing heat-related health threats in cities worldwide. In Los Angeles (LA), increasing trends in extreme heat are expected to intensify and exacerbate the urban heat island effect, leading to greater health risks for vulnerable populations. Partnerships between city policymakers and scientists are becoming more important as the need to provide data-driven recommendations for sustainability and mitigation efforts becomes critical. Here we present a model to produce heat vulnerability index (HVI) maps driven by surface temperature data from National Aeronautics and Space Administration’s (NASA) new Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) thermal infrared sensor. ECOSTRESS was launched in June 2018 with the capability to image fine-scale urban temperatures at a 70 m resolution throughout different times of the day and night. The HVI model further includes information on socio-demographic data, green vegetation abundance, and historical heatwave temperatures from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Aqua spacecraft since 2002. During a period of high heat in July 2018, we identified the five most vulnerable communities at a sub-city block scale in the LA region. The persistence of high HVI throughout the day and night in these areas indicates a clear and urgent need for implementing cooling technologies and green infrastructure to curb future warming.

全球气候变暖和城市热岛效应的双重影响使人类社会面临的极端高温风险日益加剧，给城市人口健康和社会经济可持续发展带来严峻挑战，科学评估城市热环境下人口暴露风险已成为当前学术界关注的热点领域。论文基于ECOSTRESS地表温度数据和手机信令数据，以西安市为例，在城市地表温度和人口时空变化分析基础上，构建城市人口暴露风险评价模型，揭示精细化时空尺度上的人口暴露风险时空格局及其动态演变特征。结果表明：① 西安市夏季一天内的地表温度呈现出明显的波动特征，昼夜地表温度差异较大，白天平均温度为35.5 ℃，夜间平均温度为21.5 ℃，白天地表温度空间分布相比夜间具有更明显的空间异质性，且日内所有时刻均存在不同强度的城市热岛效应，热岛分布的变化表现出从聚集状态向离散状态再过渡至聚集状态的特征。② 西安市人口分布呈单中心结构，73.6%的人口都分布在三环以内，且沿中轴线集中的现象显著，昼夜人口形成了“白天向心、夜间离心”的分布特征。③ 人口暴露的中、高与极高风险区主要呈散点式分布在城市中心区域，且86.6%的极高风险区位于三环以内，而无风险和低风险区主要集中连片分布在城市外围。④ 导致昼夜人口暴露风险差异的不同主导类型面积占比依次为温度主导型(37.9%)>共同主导型(31.5%)>人口主导型(30.6%)。研究可为城市人口暴露风险区域的识别及制定针对性的适应性策略提供参考。

Despite the importance of urban trees' surface temperature in assessing micro-climate interactions between trees and the surrounding environment, their diurnal evolution has been largely understudied at a city-wide scale due to a lack of effective thermal observations. By downscaling ECOSTRESS land surface temperature imaginary over New York City, we provide the first diurnal analysis of city-scale canopy temperature. Research reveals a remarkable spatial variation of the canopy temperature during daytime up to 5.6 K (standard deviation, STD), while the nighttime STD remains low at 1.7 K. Further, our analysis shows that the greenspace coverage and distance to bluespaces play an important role in cooling the local canopy during daytime, explaining 25.0-41.1% of daytime spatial variation of canopy temperatures while surrounding buildings modulate canopy temperature asymmetrically diurnally: reduced daytime warming and reduced nocturnal cooling. Built on space-borne observations and a flexible yet robust statistical method, our research design can be easily transferable to explore urban trees' response to local climate across cities, highlighting the potentials of advancing the science and technologies for urban forest management.

地表温度是表征城市热环境变化的重要指标,其分布信息对监测城市热环境具有重要意义。本文首先基于2018—2023年6—8月ECOSTRESS数据,通过地表温度修正得到沈阳市四环内的昼夜地表温度;然后利用均值-标准差法和空间自相关分析法对地表温度昼夜空间特征进行提取;最后结合土地利用数据,分析不同地类对地表温度空间分布的贡献度。结果表明,沈阳市四环内地表温度呈北高南低、西高东低的形式,日间和夜间地表温度差异较大。高温区主要集中在皇姑区、大东区、沈河区西部和铁西区东部,低温区和次中温区主要集中在四环边缘;人工地表类别的地表温度大多高于自然地表类别的地表温度,建筑用地类别高温区占比最多,这是地表升温的主要因素,自然地表类别是降温的主要因素;沈阳市四环内的地表温度呈空间正相关,夜间地表温度聚集程度高于日间,且具有显著性的冷热点,地表温度昼夜变化与地表温度聚集性分布特征一致。

Land surface temperature (LST) is an important index to characterize the change of urban thermal environment, and its distribution information is of great significance for monitoring urban thermal environment. Based on ECOSTRESS data from June to August from 2018 to 2023, diurnal LST in the fourth ring road of Shenyang is obtained through the correction of LST. Mean-standard deviation method and spatial autocorrelation analysis are used to extract diurnal spatial characteristics of LST, and combined with land use data, the contribution degree of different land types to the spatial distribution of land surface temperature is analyzed. As indicated by the results, the LST in the fourth ring road of Shenyang is high in the north and low in the south, and high in the west and low in the east. There is a large difference in LST between day and night. The high temperature area is mainly concentrated in Huanggu district, Dadong district, western Shenhe district and eastern Tiexi district, while the low temperature area and the middle temperature area are mainly concentrated at the edge of the fourth ring road, the artificial LST is mostly higher than the natural LST, and the high temperature area of building land category accounted for the largest proportion, which is the main factor for the warming of LST, while the natural LST is the main factor for the cooling of LST. There are significant clustering and hot spots in the fourth ring road of Shenyang, and the diurnal variation of LST is consistent with the aggregation distribution characteristics of LST.

. There is a scientific consensus on the need for spatially detailed information on urban landscapes at a global scale. These data can support a range of environmental services, since cities are places of intense resource consumption and waste generation and of concentrated infrastructure and human settlement exposed to multiple hazards of natural and anthropogenic origin. In the face of climate change, urban data are also required to explore future urbanization pathways and urban design strategies in order to lock in long-term resilience and sustainability, protecting cities from future decisions that could undermine their adaptability and mitigation role. To serve this purpose, we present a 100 m-resolution global map of local climate zones (LCZs), a universal urban typology that can distinguish urban areas on a holistic basis, accounting for the typical combination of micro-scale land covers and associated physical properties. The global LCZ map, composed of 10 built and 7 natural land cover types, is generated by feeding an unprecedented number of labelled training areas and earth observation images into lightweight random forest models. Its quality is assessed using a bootstrap cross-validation alongside a thematic benchmark for 150 selected functional urban areas using independent global and open-source data on surface cover, surface imperviousness, building height, and anthropogenic heat. As each LCZ type is associated with generic numerical descriptions of key urban canopy parameters that regulate atmospheric responses to urbanization, the availability of this globally consistent and climate-relevant urban description is an important prerequisite for supporting model development and creating evidence-based climate-sensitive urban planning policies. This dataset can be downloaded from https://doi.org/10.5281/zenodo.6364594 (Demuzere et al., 2022a).

Rapid urbanization has resulted in a serious urban heat island effect in the Hangzhou Metropolitan Area of China during the past decades, negatively impacting the area’s sustainable development. Using Landsat images from 2000 to 2015, this paper analysed the spatial-temporal patterns in a surface urban heat island (SUHI) and investigated its relationship with urbanization. The derived land surface temperature (LST) and surface urban heat island intensity (SUHII) were used to quantify the SUHI effect. Spatial analysis was employed to illustrate the spatial distribution and evolution of a SUHI. The geographically weighted regression (GWR) model was implemented to identify statistically significant factors that influenced the change of SUHII. The results show that hot and very hot spot areas increased from 387 km2 in 2000 to 615 km2 in 2015, and the spatial distribution changed from a monocentric to a polycentric pattern. The results also indicate that high-LST clusters moved towards the east, which was consistent with urban expansion throughout the study period. These changes mirrored the intensive development of three satellite towns. The statistical analysis suggests that both population density (e.g., changes in population density, CPOPD) and green space (e.g., changes in green space fraction, CGSF) strongly affected the changes in SUHII at different stages of the urbanization process. Increasing in population density has a lastingly effect on elevating the SUHII, whereas increasing green space has a constantly significant effect in mitigating the SUHII. These findings suggest that urban planners and policymakers should protect the cultivated lands in suburbs and exurbs, and make efforts to improve the utilization efficiency of construction land by encouraging the migrating population to live within the existing built-up regions.

To identify the concentrations and sources of heavy metals, and to assess soil environmental quality, 63 soil samples were collected in Yibin City, Sichuan Province, China. Mean concentrations of As, Pb, Zn, and Cu were 10.55, 61.23, 138.88 and 56.35 mg/kg, respectively. As concentrations were comparable to background values, while Pb, Zn, and Cu concentrations were higher than their corresponding background values. Industrial areas exhibited the highest concentrations of As, Pb, Zn, and Cu, while the lowest concentrations occurred in parks. Statistical analysis was performed and two cluster groups of metals were identified with Pb, Zn, and Cu in one group and As in the other. Spatial distribution maps indicated that Pb, Zn, and Cu were mainly controlled by anthropogenic activities, whereas As could be mainly accounted for by soil parent materials. Pollution index values of As, Pb, Zn, and Cu varied in the range of 0.24-1.93, 0.66-7.24, 0.42-4.19, and 0.62-5.25, with mean values of 0.86, 1.98, 1.61, and 1.78, respectively. The integrated pollution index (IPI) values of these metals varied from 0.82 to 3.54, with a mean of 1.6 and more than 90% of soil samples were moderately or highly contaminated with heavy metals. The spatial distribution of IPI showed that newer urban areas displayed relatively lower heavy metal contamination in comparison with older urban areas.

城市通风廊道对于热岛效应、空气污染的缓解以及低碳城市建设具有重要作用。论文以合肥主城区为例，基于气象数据、基础地理信息数据、卫星遥感数据等多源数据测算城市通风指标，根据指标类型和组合设置4种情景评价体系，包括通风潜力系数(VPC)、通风潜力系数+高温(VPC+LST)、通风潜力系数+雾霾(VPC+PM2.5)、通风潜力系数+高温+雾霾(VPC+LST+PM2.5)，在此基础上利用最低成本路径模型构建通风廊道，并采取Pearson关联性模型对各情景下通风效能展开评估。结果显示：① 提出新的通风廊道构建范式“基于通风潜力系数(VPC)与气候环境指标(LST/PM2.5/LST+PM2.5)组成的复合指标评价体系构建通风廊道”并验证其具有合理性，其中通风潜力系数由天空开阔度与粗糙度长度确定，气候环境指标的选择以城市面临具体的气候环境问题为依据。② 合肥市主城区夏季与冬季主导风向分别为东南与东北风向；天空开阔度与粗糙度长度指标高值区分别分布在二环线外围与二环线内老城区；地表温度指标高值区分布在经开区与包河区；PM2.5浓度指标高值区分布在老城区、包河区、新站区与瑶海区。③ 研究构建范式下的通风廊道能够产生较高效能。其中，基于“VPC+LST+PM2.5”构建范式下的通风廊道中风速等级与地表温度、PM2.5浓度的相关系数分别为-0.75、-0.85，其绝对值高于传统基于建筑形态指标构建的通风廊道的相关系数-0.68、-0.82的绝对值。④ 合肥市主城区可划分为“1+7”的两级通风廊道管控体系，在一级和二级通风廊道管控区可采取差异化的管控方式。研究旨在从建成环境层面为城市气候适应性的提高提供策略指引。