City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied. This study presents an approach for large-scale mapping of perceptions using 12,334 window view images (WVIs) collected from actual residential properties listed on real estate platforms in Wuhan, China, representing a rarely explored form of urban view imagery that offers advantages over the rendered or simulated window views commonly examined in previous studies. Through a non-immersive virtual reality platform, we collected 27,477 pairwise comparisons across six perceptual dimensions (e.g. preference) from 304 participants based on 499 WVIs. A hybrid neural network model was trained to predict human perceptions of all crowdsourced WVIs and map their spatial distribution. Results reveal significant spatial autocorrelation with distinct hot and cold spots across the whole city. Floor level strongly influences human perceptions: while higher floors offer more preferred and extensive window views, lower-floor windows provide residents with quiet and vivid views. An inference model further shows that window view composition matters considerably: high ratios of sky, trees, and low-rise buildings enhance people’s preferences and perceptions of vividness, whereas high ratios of high-rise buildings increase perceptions of monotony and oppression. Importantly, these effects are non-linear: the excessive presence of certain elements can alter their impact on human perception. This work advances urban-scale understanding of residents’ visual experiences and offers a transferable, human-centric method to inform urban planning and design aimed at improving the visual quality of window views.

Window views significantly influence residential quality and real estate value, particularly in high-rise residential buildings. Previous studies have predominantly focused on water and green views, resulting in a lack of clarity regarding the influence of other types of views on house prices. In this study, we quantified and analyzed the impacts of 9 window view elements, including sky, high-rise buildings, low-rise buildings, trees, grass, water, hard ground, roads, and barren land, on housing prices using online real estate images and computer vision techniques. Focusing on high-rise buildings constructed in the past five years, our findings, based on spatial hedonic pricing models, reveal that an increased proportion of water views through windows has a significant positive effect on property prices. Conversely, the presence of grass and hard ground is associated with significant negative impacts. This study examines the influence of various window view elements on apartment prices, offering valuable insights for urban planning, architectural design, and property development.

In recent years, landscape pattern optimization has been regarded as a cutting-edge science in various fields, and basin hydrology is no exception. Its effect on basin water purification has also been focused on. Based on the analysis of land use types and landscape patterns in the Danjiangkou Reservoir Basin, and combined with the determination of water quality indicators in the Danjiangkou Reservoir Basin, the relationship between the spatial pattern of Landscape Morphology and water quality was studied; It is found that among the basic characteristic indicators of many basins, the main influencing factors of water quality with high Variable importance for the projection (VIP>1) are IJI (Interspersion and Juxtaposition Index), COHE (Patch Cohesion Index), AI (Aggregation Index), PD (Patch Density), ED (Edge Density); Using PLSR (Partial Least Squares Regression) analysis, the main influencing factors of water quality were discussed. It was found that there was a significant negative regression relationship (Rc < 0) with CODMn (permanganate index), TP (Total Phosphorus), TN (Total Nitrogen) and NH4+-N (ammonia nitrogen) in the basin, and the influencing factors were topographic humidity index, topographic relief, slope, and forest area; The landscape patch connectivity index was used to determine the ecological source areas in the Danjiangkou reservoir basin that have improved connectivity and need to be protected; The priority of ecological corridor construction and protection was determined; With the help of the minimum cumulative resistance model, the ecological corridor between various ecological sources is constructed; The ecological grips on the ecological corridor are identified. In order to provide technical support for the optimization of landscape configuration for the purpose of water quality purification in Danjiangkou reservoir area.

The central areas of many Chinese cities have experienced large-scale urbanization in recent decades, a trend that is affecting the quality of life of residents and posing challenges to the sustainable development of urban ecosystems. Hence, it is vital to conduct assessments of urban ecosystems’ health conditions to ensure their sustainability. In this study, the spatial and temporal dynamics of ecosystem health in the central city of Wuhan were analyzed using the Vigor-Organization-Resilience-Service (VORS) model. The sensitivity of ecosystem health at different scales was also investigated using hierarchical health assessment delineation and random forest regression methods. The results showed that the composite index of ecosystem health has been declining since 2000, highlighting the negative impacts of shrinking ecological space, declining service capacity and urban expansion. Health zoning divides areas into five categories. Meanwhile, the health zones are located in areas of dense shrubs, cropland and water bodies on the edge of the central city, while the weak zones are mainly in the core of the city, which is 99.33 % impervious surface. The main factors influencing ecosystem health, including impervious surface area, water bodies and topography, vary from region to region. The study proposes targeted ecological management strategies for different health zones in Wuhan, emphasizing ecosystem protection and providing guidance for sustainable urban development.

Climate dictates wildfire activity around the world. But East and Southeast Asia are an apparent exception as fire-activity variation there is unrelated to climatic variables. In subtropical China, fire activity decreased by 80% between 2003 and 2020 amid increased fire risks globally. Here, we assessed the fire regime, vegetation structure, fuel flammability and their interactions across subtropical Hubei, China. We show that tree basal area (TBA) and fuel flammability explained 60% of fire-frequency variance. Fire frequency and fuel flammability, in turn, explained 90% of TBA variance. These results reveal a novel system of scrubland–forest stabilized by vegetation–fire feedbacks. Frequent fires promote the persistence of derelict scrubland through positive vegetation–fire feedbacks; in forest, vegetation–fire feedbacks are negative and suppress fire. Thus, we attribute the decrease in wildfire activity to reforestation programs that concurrently increase forest coverage and foster negative vegetation–fire feedbacks that suppress wildfire.

Urban areas are significant centers of human activity and are recognized as major contributors to global carbon emissions. The establishment of urban green spaces plays a crucial role in enhancing carbon sinks and mitigating carbon emissions, thereby fostering a low-carbon cycle within cities. However, the existing literature on the carbon sequestration of green spaces in Chinese cities often overlooks the role of water bodies, which are a significant characteristic of wetland cities. Therefore, it is necessary to investigate the carbon sequestration potential of green spaces in wetland cities, taking into account the contribution of water bodies to carbon sinks. This study aims to analyze the quantitative structure of urban green spaces through the lens of carbon balance, which can effectively enhance a city’s overall carbon sequestration capacity. Utilizing carbon balance theory, this research first assesses the carbon offsetting capability (COC) of urban green spaces in Wuhan for the year 2019. It then forecasts future carbon emissions, sets improvement targets for COC, and calculates the required area of standard green space to achieve these targets by 2030. A multi-objective programming (MOP) model is developed to identify the optimal solution that aligns with urban development planning constraints while maximizing carbon sinks. Lastly, we analyzed the contribution rates of different types of urban green spaces to the total carbon sequestration capacity of green spaces to clarify the characteristics of carbon absorption in green spaces of Wuhan, a wetland city. The findings indicate the following: (1) In 2019, Wuhan’s carbon emissions from human activities reached approximately 38.20 Mt, with urban green spaces absorbing around 5.62 Mt of carbon, and a COC of about 14.71%. (2) Projections for 2030 suggest that carbon emissions in Wuhan will rise to approximately 42.64 Mt. Depending on the targeted COC improvement rates of 5%, 10%, 15%, 20%, and 25%, the required values of carbon sequestration will be 6.59 Mt, 6.90 Mt, 7.21 Mt, 7.53 Mt and 7.84 Mt, respectively. (3) The results of the MOP model indicate that the optimal COC for 2030 is projected to be 16.33%, which necessitates a carbon sequestration of 6.97 Mt. (4) Water bodies accounted for 56.23% of the total carbon absorption in green spaces in 2019 and are projected to represent 45.37% in 2030, highlighting the distinctive characteristics of Wuhan as a wetland city in terms of its green space carbon sequestrations. The management and enhancement of water body carbon sequestration capacity is crucial for the carbon sequestration potential of urban green space in Wuhan. The results of this study can provide evidence and recommendations for the low-carbon development patterns of wetland cities across China.

ContextTrees play a vital role in reducing street-level particulate matter (PM) pollution in metropolitan areas. However, the optimal tree growth type for maximizing the retention of various sizes of PM remains uncertain.ObjectivesThis study assessed the PM reduction capabilities of evergreen and deciduous broadleaf street trees, focusing on how leaf phenology influences the dispersion of pollutants across particle sizes.MethodsWe collected data on six PM size fractions from 72 sites along streets lined with either evergreen or deciduous broadleaf trees in Wuhan, China, during the summer and winter of 2017-2018.ResultsEvergreen trees demonstrated superior PM reduction capabilities compared to deciduous trees, with evergreen street canyons showing 27.2% and 12.6% lower PM2.5 and PM10 concentrations in summer, and 13% and 5.5% lower concentrations in winter. During summer, evergreen streets predominantly contained fine particles (PM1, PM2.5), posing potential health risk due to their ability to infiltrate the human respiratory system. In contrast, deciduous streets primarily harbored coarser particles (PM4, PM7, PM10, and total suspended particulate [TSP]). During winter, larger particles were dominant, regardless of the tree growth form.ConclusionsEvergreen trees showed superior PM reduction capabilities compared to deciduous trees due to their year-round leaf retention, enhanced surface properties, and denser canopies that maximize PM capture. We recommend prioritizing evergreen broadleaf trees as the primary street trees while interspersing deciduous trees at appropriate intervals. This approach will ensure that urban greenery provides maximum ecological benefits while reducing the PM concentration.

The escalation of thermal risks is attributed to accelerating pace of urbanization. However, assessment and response to green infrastructure with respect to heat risk under different climate and function have been inadequate. This study intends to address these gaps by focusing on local climate zones (LCZs). Firstly, spatial characteristics of heat risk indexes (HRIs) constructed based on heat hazard-exposure-vulnerability for three large cities in 2010, 2015 and 2020 were explored. Secondly, whether HRI cross LCZs have significant differences was examined. Third, proportion and heat contribution of different HRI classes under different LCZs were quantified. Finally, effects of green infrastructure under different LCZs on HRI were analyzed. The results revealed consistent upward trends in the prevalence of sub-high and high HRIs from 2010 to 2015. HRIs exhibited significant spatial aggregation characteristics. Importantly, more than 95.83% of HRIs cross LCZs exhibited significant variations. The HRI for open building type was lower when compared to the compact LCZ types. Additionally, Normalized Difference Vegetation Index (NDVI) had a more pronounced mitigating effect on HRIs in compact high-rise (LCZ 1), compact mid-rise (LCZ 2), open high-rise (LCZ 4) and open mid-rise (LCZ 5). Updating the compact LCZ types to open LCZ types, avoiding configuration of LCZ 1 and 2, and prioritizing the configuration of NDVI enhancement in the existing LCZ 1, 2, 4 and 5, and increasing the amount of greenery by upgrading mono-structures to composite structures consisting of trees, shrubs and grasses and by implementing greening of façade are suggested to alleviate heat risk.

When developing strategies aimed at mitigating air pollution in densely populated urban areas, it is vital to accurately investigate the vertical distribution of airborne particulate matter (PM) and its primary influencing factors. For this study, field experiments were conducted to quantify the vertical distribution and dispersion processes of PM at five vertical heights related to trees—including at street level near vehicular emission sources (0.3 m), pedestrian breathing height (1.5 m), beneath the canopy (6 m), mid-canopy (9 m), and the top of the canopy (12 m)—within a street-facing building in Wuhan, China. Comparing the vertical dispersion patterns of PM with six particle sizes (PM1, PM2.5, PM4, PM7, PM10, and total suspended particulates—TSPs), larger particles exhibited more pronounced variations with height, notably TSPs (correlation coefficient of −0.95) and PM10 (−0.84). The findings consistently revealed a downward trend in PM concentrations across various particle sizes with increasing height, indicating a negative linear correlation between particle concentrations and altitude within the street canyon. For every 1% increase in vertical height, the PM2.5 concentration decreased by approximately 5.44%, the PM10 concentration decreased by 132.1%, and the TSP concentration decreased by 180.6%. These findings show potential for guiding building designers in developing effective strategies, such as optimal vent placement, in order to mitigate the intrusion of outdoor air pollution—particularly PM2.5—into indoor environments. Furthermore, this research provides novel insights for residents living in street-facing buildings and individuals with respiratory diseases, aiding them in the selection of residential floors to minimize health risks associated with exposure to respirable PM.

Time-varying characteristics of particulate matter (PM) pollution play a crucial role in shaping atmospheric dynamics, which impact the health and welfare of urban commuters. Previously published studies on the diurnal patterns of PMs are not consistent, especially in the context of field experiments in central China, and most field studies have only focused on particles with a single particle size. This study conducted regional-scale studies across 72 street canyon sets in Wuhan, China, investigated diurnal and seasonal PM concentration variations while also evaluating various PM size and the key driving factors. During summer (July, August, and September), evergreen tree-lined street canyons maintained a stable linear trend for smaller dp particulates (i.e., PM1, PM2.5, and PM4), while deciduous street canyons exhibited a bimodal distribution. In winter (January and February), fine particulates (i.e., PM1 and PM2.5) remained a linear trend in evergreen street canyons, while deciduous street canyons show a slightly wavy fluctuating pattern. Meanwhile, it exhibited quadrimodal-peak and triple-trough patterns in both PM7, PM10, and TSP concentrations. The lowest PM concentrations were observed between 14:00 and 16:00 for all particle sizes, with decreased summer pollution (7.81% lower in PM2.5, 53.47% lower in PM10, and 50.3% lower in TSP) noted in our seasonal analysis. Among the various meteorological factors, relative humidity (RH) was identified as the dominant influencing PM factor in both summer and winter. Results from this study will help us better understand field-based air pollutant dispersion processes within pedestrian spaces while laying the groundwork for future research into street PM experiments.

According to previous hydrology studies, both the land-use type and the spatial pattern of landscapes affect the quality of water in river basins. However, demonstrating and quantifying the effects of landscape patterns on water quality remain challenging. The present study was conducted in the water source protection zone of Danjiangkou in Hubei Province, China. Based on locations of water quality monitoring stations in the area of the reservoir and the hydrological analysis module in the ArcGIS software, the study area was divided into 10 sub-basins. The "source-sink" landscape pattern obtained from land use/land cover (LULC) analysis of the sub-basins was then used as the medium. Binary data characterized as foreground and background required for morphological spatial pattern analysis (MSPA) corresponded to source and sink landscape types. Partial least squares regression (PLSR) analysis of water quality and the MSPA data were integrated to comprehensively evaluate the impacts of land-use types and landscape pattern changes on water quality in the basin. The results show that land use, landform and spatial landscape pattern have a important impact on the water quality of the watershed. When using the PLSR model based on the "source-sink" morphological spatial pattern to predict water quality, compared to the model analysis solely based on LULC, the MSPA based PLSR improves the principal component grouping, x-variable interpretation rate, y-variable interpretation rate (R2), model prediction rate (Q2), and model prediction accuracy. This study shows that that landscapes is demonstrated to affect water quality and that the use of multiple methods -PLSR, LULC and MSPA data -is a useful complement to hydrological literature. PLSR modeling combined with LULC analysis and MSPA data can accurately predict the water quality of the basin. The use of this improved model for water quality prediction is the focus of this study.

Urban heat islands are representative problems in urban environments. The impact of spectral indexes on land-surface temperature (LST) under different urban forms, climates, and functions is not fully understood. Local climate zones (LCZs) are used to characterize heterogeneous cities. In this study, we quantified the contribution of three cities to high-temperature zones and surface urban heat island intensity (SUHII) across LCZs and seasons, used Welch and Games–Howell tests to analyze the difference in LST, then described the spatial pattern characteristics of LST, and used a geographically weighted regression model to analyze the relationship between spectral indexes and LST. The results showed that compact midrise, compact low-rise (LCZ 3), large low-rise (LCZ 8), heavy industry (LCZ 10), and bare rock or paved (LCZ E) contributed greatly to high-temperature zones and had strong SUHII. There were 92–98% significant differences between different LCZs. The spatial aggregation of LST gradually weakened with a decrease in temperature. The modified normalized difference water index (MNDWI) in most LCZs of all seasons for Wuhan could reduce LST well, while MNDWI only had cooling effects in winter for Nanjing and Shanghai. Normalized difference vegetation index (NDVI) in most LCZs performed a cooling role during summer and transition seasons (spring and autumn), while it showed a warming effect in winter. The cooling effect of NDVI in open building types was stronger than that of compact building types, while the cooling effect of MNDWI was better in compact building types than in open building types. With the increase of normalized difference built-up index (NDBI), all LCZs showed warming effects, and the magnitude of LST increase varied in different cities and seasons. These results contribute further insight into thermal environment in heterogeneous urban areas.

Urban blue spaces (UBS) have been shown to provide a multitude of cultural ecosystem services to urban residents, while also having a considerable impact on the surrounding community's house prices. However, the impact of different types of UBS and the effect of their abundance on house prices have been largely understudied. This study aims to address this gap by examining the impact of different types of UBS on house prices using eight megacities in China as a case study. Spatial hedonic price models are developed to assess the impact of different types of UBS on house prices, and differences in their impact across cities are identified. Variance partitioning analysis is also used to decompose the relative contributions of UBS variables and explore the relationship between UBS-attributable premiums and the abundance of UBS. The results indicate that lakes and the main river have a significant positive impact on house prices in most cities, while the impact of small rivers on house prices varies across cities. The influence of UBS variables differs significantly across cities, but these differences are not solely driven by the abundance of UBS. This study provides valuable information for UBS planning and management and contributes to the equitable distribution of urban public services.

IntroductionThe factors that determine the growth and spread advantages of an alien plant during the invasion process remain open to debate. The genetic diversity and differentiation of an invasive plant population might be closely related to its growth adaptation and spread in the introduced range. However, little is known about whether phenotypic and genetic variation in invasive plant populations covary during the invasion process along invaded geographic distances.MethodsIn a wild experiment, we examined the genetic variation in populations of the aggressively invasive species Erigeron annuus at different geographical distances from the first recorded point of introduction (FRPI) in China. We also measured growth traits in the wild and common garden experiments, and the coefficient of variation (CV) of populations in the common garden experiments.Results and discussionWe found that E. annuus populations had better growth performance (i.e., height and biomass) and genetic diversity, and less trait variation, in the long-term introduced region (east) than in the short-term introduced region (west). Furthermore, population growth performance was significantly positively or negatively correlated with genetic diversity or genetic variation. Our results indicate that there was parallel genetic and phenotypic differentiation along the invaded geographic distance in response to adaptation and spread, and populations that entered introduced regions earlier had consistently high genetic diversity and high growth dominance. Growth and reproduction traits can be used as reliable predictors of the adaptation and genetic variation of invasive plants.

全球新技术革命和产业变革以及我国的国家发展战略都对高校的专业建设和人才培养提出了新的要求.在此背景下启动的"新农科"建设对林学类人才的培养提出了更新更高的要求,林学专业的人才培养目标和培养路径也随之有所改变.传统的林学专业人才培养体系主要存在对新时代背景下的林学专业人才培养目标及其内涵认识不足、专业课程体系设置不够合理、教学方法仍以灌输式为主、教学管理体制弹性不足、缺乏对学习过程的全面考核、实践教学内容简单易行、林科教协同育人力度不够、为学生提供的拓展国际视野的空间有限、对思想政治教育的重视不够等问题,已经难以适应现代林业行业以及相关科技的快速发展,特别是难以满足"新农科"建设对林学专业人才培养的要求.为此,华中农业大学从"新农科"建设的角度出发,提出林学专业人才培养体系改革的思路,并着重从以下方面进行了改革探索.一是深刻领悟新时代林学专业人才培养的 目标要求及其内涵,以培养高素质创新型或复合型专业人才为 目标,构建"听、学、练、考、创"五位一体的人才培养方案.二是以"三全育人"和课程群建设为核心,构建包括微观、中观和宏观等不同尺度课程群的课程体系.三是推动课堂教学方式改革,构建包括国家、学校、学院3个层级的创新训练体系,落实本科生导师制,加强教学与科研的融合.四是建立多元化的教学质量监控机制、教学过程考核制度、教学奖惩制度等.五是构建具有区域特色的林学专业实践教学平台,形成全方位全过程的林科教协同育人新机制.六是加强与国内外一流涉农类高校或研究机构等的交流合作.实践证明,"新农科"视域下林学专业人才培养体系改革取得了一定成效.

城市热岛是城市环境中的典型问题.景观指数影响范围的空间异质性很少被理解.为了解决这个问题,拟采用多尺度地理加权回归模型(MGWR)来分析景观指数,归一化差值植被指数(NDVI)与地表温度(LST)之间的相互关系.结果显示,和普通最小二乘法回归和地理加权回归相比较,MGWR揭示了不同景观指数的空间影响尺度,具有更接近真实值的拟合效果.增加绿地和水体景观百分比及NDVI能够很好地缓解LST,其他景观指数则与LST的关系在不同的位置呈现正或负相关,需在特定位置进行优化才能有效地缓解LST.总的来说,形状简单且聚集分布的较大绿地斑块和形状复杂且较小的绿地斑块,以及在大多数情况下形状复杂、连通性强的水体景观更利于缓解LST.

Numerous empirical studies have demonstrated that street trees not only reduce dust pollution and absorb particulate matter (PM) but also improve microclimates, providing both ecological functions and aesthetic value. However, recent research has revealed that street tree canopy cover can impede the dispersion of atmospheric PM within street canyons, leading to the accumulation of street pollutants. Although many studies have investigated the impact of street trees on air pollutant dispersion within street canyons, the extent of their influence remains unclear and uncertain. Pollutant accumulation corresponds to the specific characteristics of individual street canyons, coupled with meteorological factors and pollution source strength. Notably, the characteristics of street tree canopy cover also exert a significant influence. There is still a quantitative research gap on street tree cover impacts with respect to pollution and dust reduction control measures within street spaces. To improve urban traffic environments, policymakers have mainly focused on scientifically based street vegetation deployment initiatives in building ecological garden cities and improving the living environment. To address uncertainties regarding the influence of street trees on the dispersion of atmospheric PM in urban streets, this study reviews dispersion mechanisms and key atmospheric PM factors in urban streets, summarizes the research approaches used to conceptualize atmospheric PM dispersion in urban street canyons, and examines urban plant efficiency in reducing atmospheric PM. Furthermore, we also address current challenges and future directions in this field to provide a more comprehensive understanding of atmospheric PM dispersion in urban streets and the role that street trees play in mitigating air pollution.

Negative impacts of urban heat island (UHI) are exacerbated by rapid urbanization. To address insufficient on construction of key areas for UHI mitigation, source-sink theory and local climate zone (LCZ) were developed to build networks. This study discriminated source and sink landscapes, and applied multiple spatial analyzes to identify key surfaces, corridors and barrier points of heat source and sink landscapes at urban and main urban district scales. 30 important heat source and sink landscape surfaces were identified, primarily comprised open high-rise and open mid-rise in heat source landscapes, accounting for 34.07%, 22.19% at urban scale, and 48.63%, 29.68% at main urban scale, composed of low plants and water in heat sink landscapes, representing 68.63%, 12.28%, and 45.99%, 31.80%, respectively. 62 and 58 heat source corridors identified were dominated by open high-rise, and low plants, accounting for 16.02%, 31.67%, and 21.70%, 22.41%. 60 and 46 heat sink corridors identified composed of open high-rise, low plants, and water, with percentages of 19.94%, 41.13%, 13.25%, and 32.97%, 30.09%, 7.42%, respectively. Barrier points of 38 and 28 heat source landscapes identified were characterized mainly by low plants, and water, representing proportions of 52.10%, 20.24%, and 42.73%, 18.31%, respectively. Barrier points of 41 and 20 heat sink landscapes identified were primarily associated with open high-rise, open mid-rise accounting for proportions of 41.17%, 20.03%, and 54.17%, 18.89%, respectively. Given these key areas, it is recommended to split heat source landscape, increase area of smaller sink landscape, renew of LCZs to those with lower UHI intensity.

随着"互联网+"新经济模式的发展,数字化、网络化、智慧化成为各个行业新的发展契机.随着"智慧林业"的提出,智慧林业人才培养被纳入林学专业人才培养计划.本文在调研就业市场对智慧林业人才的需求、学生对信息技术的了解和掌握程度的基础上,分析了 18所林业院校中林学专业关于信息技术类相关课程的设置和实践情况,并以华中农业大学林学专业的智慧林业人才培养模式为例,基于智慧林业人才核心技能需求,提出了多学科交叉融合的智慧林业人才培养思路和实现路径.

交通和工业排放是大气污染的主要来源.先前研究并未充分理解剔除交通和工业排放前后绿地景观格局对气溶胶光学厚度(AOD)的影响,比较分析了疫情封城前后社会经济、路网密度、绿地景观指数与AOD之间的因果关系,采用随机森林量化不同绿地景观百分比下影响AOD的主导因子,探测绿地景观指数和AOD的空间自相关特征,然后采用多尺度地理加权回归来量化绿地景观指数对AOD的影响.结果表明,在不同绿地景观百分比和疫情封城前后影响AOD的主导因子具有差异.与疫情封城之前相比较,封城后绿地景观指数削减气溶胶污染的能力被减弱了,但影响因子对AOD的相对重要性得到了增强.绿地景观指数和AOD均存在显著的空间集聚特征.绿地景观指数在疫情封城前后对AOD的影响大小和尺度存在差异.研究结果有助于基于缓解AOD下绿地景观格局优化和政策制定.