Exploring the spatiotemporal relationship between green infrastructure and urban heat island under multi‐source remote sensing imagery:A case study of Fuzhou City

Green Infrastructure(GI)has garnered increasing attention from various regions due to its potential to mitigate urban heat island(UHI),which has been exacerbated by global climate change.This study focuses on the central area of Fuzhou city,one of the“furnace”cities,and aims to explore the correlation between the GI pattern and land surface temperature(LST)in the spring and autumn seasons.The research adopts a multiscale approach,starting from the urban scale and using urban geographic spatial characteristics,multispectral remote sensing data,and morphological spatial pattern analysis(MSPA).Significant MSPA elements were tested and combined with LST to conduct a geographic weighted regression(GWR)experiment.The findings reveal that the UHI in the central area of Fuzhou city has a spatial characteristic of“high temperature in the middle and low temperature around,”which is coupled with a“central scattered and peripheral concentrated”distribution of GI.This suggests that remote sensing data can effectively be utilised for UHI inversion.Additionally,the study finds that the complexity of GI,whether from the perspective of the overall GI pattern or the classification study based on the proportion of the core area,has an impact on the alleviation of UHI in both seasons.In conclusion,this study underscores the importance of a reasonable layout of urban green infrastructure for mitigating UHI.

Analysis of the Spatio-Temporal Characteristics of Winter Surface Urban Heat Island:A Case Study in Beijing,China

This study reveals the temporal and spatial evolution characteristics of the winter nighttime urban heat island(UHI)effect in the case of Beijing,China.The land surface temperature(LST)is retrieved by radiative transfer equation by using the remote sensing data from Landsat ETM+/OLI_TIRS from 2007 to 2017 for the winter nighttime period,and LST is then divided by the mean-standard deviation method into different levels of thermal landscapes.A combination of the migration calculation of gravity center and multi-directional profile analysis is used to study the directional differentiation characteristics of LST and the migratory characteristics of the gravity center of UHI.Finally,the overall temporal and spatial evolution characteristics of winter nighttime surface urban heat island(SUHI)in Beijing are studied,and the possible reasons for the changes are discussed.Results show that Beijing's UHI effect first increased and subsequently decreased from 2007 to 2017.The winter heat island in the urban area developed from low-density agglomeration to high-density agglomeration to lowdensity diffusion.Additionally,the high-level thermal landscapes migrated to the southwest along with the city center of gravity,and the expansion rate is fastest in the southwest,which is directly linked to the changes in the urban construction land.Moreover,the overall spatial distribution of winter nighttime LST is high in the east and south and low in the west and north,and is influenced by topography,land cover,urbanization,anthropogenic heat,and other factors as well.

Predicting Surface Urban Heat Island in Meihekou City, China: A Combination Method of Monte Carlo and Random Forest

Given the rapid urbanization worldwide, Urban Heat Island(UHI) effect has been a severe issue limiting urban sustainability in both large and small cities. In order to study the spatial pattern of Surface urban heat island(SUHI) in China’s Meihekou City, a combination method of Monte Carlo and Random Forest Regression(MC-RFR) is developed to construct the relationship between landscape pattern indices and Land Surface Temperature(LST). In this method, Monte Carlo acceptance-rejection sampling was added to the bootstrap layer of RFR to ensure the sensitivity of RFR to outliners of SUHI effect. The SHUI in 2030 was predicted by using this MC-RFR and the modeled future landscape pattern by Cellular Automata and Markov combination model(CA-Markov). Results reveal that forestland can greatly alleviate the impact of SUHI effect, while reasonable construction of urban land can also slow down the rising trend of SUHI. MC-RFR performs better for characterizing the relationship between landscape pattern and LST than single RFR or Linear Regression model. By 2030, the overall SUHI effect of Meihekou will be greatly enhanced, and the center of urban development will gradually shift to the central and western regions of the city. We suggest that urban designer and managers should concentrate vegetation and disperse built-up land to weaken the SUHI in the construction of new urban areas for its sustainability.

Impact of Local Climate Zones on the Urban Heat and Dry Islands in Beijing:Spatial Heterogeneity and Relative Contributions

Based on the building height and density data on a 100-m resolution,hourly 2-m temperature and humidity data at83 automatic weather stations,and gridded local climate zone(LCZ)data on a 120-m resolution in urban Beijing in2020,this study first employs the semivariogram combined with building parameters to calculate spatial correlations and has identified an LCZ grid resolution of 500 m suitable for best usage of the available observation data.Then,how the spatially heterogeneous LCZs affect and contribute to the canopy urban heat island intensity(UHII)and urban dry island intensity(UDII)are quantitatively investigated.It is found that UHII is high in winter and low in summer with a unimodal diurnal variation while UDI is low in winter but high in summer with a bimodal diurnal variation.The LCZ with compact mid-rise(open high-rise)buildings exhibits the highest UHII(UDII),followed by the compact high-rise(compact low-rise),while the LCZ of scattered trees presents both the lowest UHII and the lowest UDII.The most significant difference in the UHII(UDII)among the nine LCZ types in the urban area of Beijing is2.62℃(1.1 g kg^(-1)).Area-weighted averaging analysis reveals that the open mid-rise LCZ is the most significant contributor to the UHII(UDII),immediately followed by compact mid-rise(open low-rise),with the least contribution from bare rock or paved(scattered trees).The results also indicate that beyond the intrinsic physical properties of the LCZs of a city,their area proportions cannot be overlooked in evaluating their impact on the UHI and UDI.These quantitatively findings could help urban planners to create a livable urban climate and environment by adjusting the relevant land use.

城市蓝绿空间对热岛的温度影响分析

为研究蓝绿空间与城市热环境之间的相互关系,文章以哈尔滨主城区为研究区,以城市热岛作为研究对象,从降温幅度及降温范围两个方面探究蓝绿空间对周围环境温度的影响,构建了蓝绿空间热环境拟合模型。研究结果表明:(1)城市蓝绿空间对四周温度的影响可通过六次多项式进行表示;(2)蓝绿空间的下垫面类型、面积、景观指数等指标会在不同程度影响温度。

Exploring diurnal and seasonal variabilities in surface urban heat island intensity in the Guangdong-Hong Kong-Macao Greater Bay Area

The urban heat island(UHI) is an environmental problem of wide concern because it poses a threat to both the human living environment and the sustainable development of cities. Knowledge of the spatiotemporal characteristics and the driving factors of UHI is essential for mitigating their impact. However, current understanding of the UHI in the Guangdong–Hong Kong–Macao Greater Bay Area(GBA) is inadequate. Combined with data(e.g., land surface temperature and land use.) acquired from the Google Earth Engine and other sources for the period 2001–2020, this study examined the diurnal and seasonal variabilities, spatial heterogeneities, temporal trends, and drivers of surface UHI intensity(SUHII) in the GBA. The SUHII was calculated based on the urban–rural dichotomy, which has been proven an effective method. The average SUHII was generally 0–2°C, and the SUHII in daytime was generally greater than that at night. The maximum(minimum) SUHII was found in summer(winter);similarly, the largest(smallest) diurnal difference in SUHII was during summer(winter). Generally, the Mann–Kendall trend test and the Sen's slope estimator revealed a statistically insignificant upward trend in SUHII on all time scales. The influence of driving factors on SUHII was examined using the Geo-Detector model. It was found that the number of continuous impervious pixels had the greatest impact, and that the urban–rural difference in the enhanced vegetation index had the smallest impact, suggesting that anthropogenic heat emissions and urban size are the main influencing factors. Thus, controlling urban expansion and reducing anthropogenic heat generation are effective approaches for alleviating surface UHI.

绿色空间景观格局对热环境的影响研究——以北京市平原地区为例

在城市高密度建设、热环境恶化的背景下,绿色空间格局对调控热环境、保障健康人居环境起重要作用。研究基于北京市平原地区的Landsat遥感数据,运用监督分类、景观生态学理论及统计分析方法,揭示了绿色空间格局与平原地区热环境的耦合关系。结果显示:(1)MSPA分析显示总体降温效果,支线>桥接>边缘>核心>孔隙>环道>孤岛;(2)核心、环道、边缘型绿色空间随着绿量的减少和破碎化,其降温效果逐年下降;(3)孤岛型绿色空间的降温效果逐年增加,桥接和支线型绿色空间的降温效果则更为稳定;(4)北京市平原地区的线状绿色空间在近二十年发挥的作用大于面状、点状。研究可为北京市应对气候变化、优化平原地区的绿色空间格局提供理论参考。

GI格局影响区域气温的尺度效应和空间分异特征——基于天津市的实证

绿色基础设施为应对气候变化提供了一种基于自然的解决方案,尤其在调节区域气温方面发挥着重要作用。既有关于绿色基础设施与区域气候关联性的研究主要关注规模数量对全局尺度气候因子的影响,对尺度变化及其空间异质性的讨论不足。以天津市为例,综合运用景观生态学和地理加权回归分析方法,在测度研究区绿色基础设施格局的基础上,深入探讨了绿色基础设施格局影响区域气温的尺度效应和空间作用规律。结果表明:1)绿色基础设施格局能够显著影响区域气温,且随着尺度增加各项格局指数与区域气温的相关程度均呈现先增大后减小的趋势,并在7km×7km尺度下达到峰值;2)各项格局指数与区域气温的相关程度整体上为面积类指数>聚集类指数>密度类指数>形状类指数;3)各项格局指数与区域气温的相关性具有空间非稳定性特征,其中半城市化地区的区域气温更易受到格局变化的影响。最后,提出以乡镇(街道)为单元的GI格局分区优化措施,以期为气候适应性规划设计和各类相关政策的制定提供科学指导。

Street network patterns for mitigating urban heat islands in arid climates

This study explores the impact of street pattern measurements on urban heat islands(UHI)in the arid climate of Mashhad,Iran.The Landsat-8 top-of-the-atmosphere(TOA)brightness images from 2013 to 2021,average values of normalized difference vegetation index(NDvI)and land surface temperature(LST)were calculated.Street pattern measurements,including closeness-centrality,straightness,and street orientation,were employed to analyse the patterns in each district.The results indicated that districts with higher straightness and lower closeness-centrality exhibit,cooler surface temperatures.Strong correlations were observed between LST and NDVl,straightness,and local closeness-centrality.The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions.A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably.Street pattern indexes,such as straightness and local closeness-centrality,are identified as significant factors in urban design to mitigate UHl.These findings have implications for urban planners,who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness.

基于MSPA模型的新型城市热景观连通性分析

基于土地利用景观格局对城市热岛效应的影响研究较多,但准确识别对城市热岛效应具有重要影响的关键斑块和节点方面的研究亟待开展。以新型中小城市株洲云龙示范区为例,以城市热岛网络构建为切入点,应用形态学空间格局分析(Morphological Spatial Pattern Analysis,MSPA)与景观连通性模型识别城市发展进程中核心热景观斑块和关键节点,并分析其时空演变特征。研究结果表明:(1)2007—2018年云龙示范区热岛斑块趋于集中,热岛面积较研究初期有明显增加,从地表温度空间分布上体现为城区与周边农村的温度对比更加鲜明,表明城市化进程中建设用地呈聚集扩散趋势。(2)研究期间热岛核心区占热景观面积比最大,且比例有明显上升趋势。而边缘、支线、孤岛、桥接、环线以及孔隙形态类型面积占比均呈现出不同程度的下降趋势,表明热岛斑块之间聚集程度不断提高。(3)识别出景观连通度重要性值较高的前20热景观斑块,其中前3斑块的重要性值和面积占比较大,属于极重要与重要两个热岛核心斑块重要性等级,值得重点关注与优化。(4)对重要性值高的热岛核心区域可优先采取降温措施,可以打断节点之间连接减缓整个区域的热岛效应。本研究结果对我国中小城市规划和可持续发展具有重要的实践指导意义。

共享社会经济路径下中国城市热岛时空演变及预测研究

人类活动已被认为是造成城市热岛效应的关键因素。然而市域尺度下人为因素对热岛效应强度的影响尚不明确。基于多源地理数据计算了2012—2018年中国市域尺度的日间地表城市热岛效应强度(SUHI),分析了市域尺度SUHI的时空演变规律和驱动机制,并构建驱动因子与SUHI的关系模型;结合IPCC提出的共享社会经济路径(SSPs)来预测不同情景下的人类活动强度,并模拟2020—2100年的SUHI。结果表明:2012—2018年市域尺度上,年均SUHI空间分布呈现出南方整体高于北方,东南沿海最强、西北地区最弱的特征,且具有明显的正向空间自相关性,2012—2018年间SUHI有略微的增强(均值增幅达0.08℃)。SUHI受人为因素与自然因素共同影响,其中GDP及城乡植被差异(ΔNDVI)对SUHI影响显著。2020—2100年5种SSPs情景下中国大部分城市的SUHI显著增强,其中SSP5情景下SUHI变化最剧烈(均值增幅达0.67℃)。此外,大体量城市未来的SUHI在不同发展情景下差异明显。从驱动因素来看,大多数城市的GDP是SUHI增长的主要人为驱动因素。对典型城市的对比分析发现,在21世纪末上海城市群、天津市、乌鲁木齐市及南宁市的SUHI波动范围可能分别达到4.83~8.98℃、3.24~4.95℃、1.11~1.55℃、2.61~4.05℃。研究结果揭示了不同社会经济发展路径下SUHI可能的时空变化趋势,对实现城市生态环境的健康发展具有重要意义。

基于“源-汇”景观格局的城市热岛效应及影响因素分析--以合肥市为例

选择城镇化增速居长三角三省一市第一位的合肥市作为研究区,通过提取植被指数、湿度指数、不透水面指数等地表特征敏感的遥感指数和地表温度来识别城市热岛的“源-汇”景观,结合土地利用类型对“源”景观贡献度及城市热岛效应进行研究.结果表明:合肥市热岛“源”景观的升温影响范围为150m,“源-汇”景观格局能有效缓解城市热岛效应,缓解程度由东南至西北呈强至弱的趋势,庐江县、巢湖市的缓解效果最好,蜀山区、瑶海区的缓解效果最差;“源-汇”景观面积的比值、“源”景观的有效粒径尺度越小,“源”景观的标准形状指数在0~0.35且景观斑块越离散,热岛效应的缓解程度越好;对任何地物斑块而言,热岛效应导致的温度上升都会削弱“源-汇”景观格局对热岛效应的抑制效率,增加林地的覆盖是减轻区域升温、缓解区域热岛的有效手段之一.

城市公园景观格局对热岛效应的影响研究进展

城市绿地是缓解城市热岛效应的重要方式之一,以往研究多聚焦于城市绿地对周边热环境的影响,较少关注城市公园内外部景观格局差异对于城市热岛效应的影响。对国内外相关文献进行文献调研,通过整合分析,从研究趋势、研究手段、研究成果三方面进行归纳,探讨了公园内部景观斑块,公园总体形态特征,不同研究区、研究方法、研究指标对于结果产生的可能性影响。分析发现,公园内部景观类型所占比例与公园总体形态特征对热岛效应缓解程度和辐射范围不同;其次研究区所处位置、不同研究方法和选取不同评价指标也会对研究结果产生影响。已有的研究对于城市公园和热岛效应相关性关注较少,并且不同研究区在温度带和干湿区域方面的差异导致研究结果呈现多样性,仍需对于不同条件下的城市公园开展本土研究,并分析其对热岛效应的缓解程度,为未来城市公园的规划布局,建设绿色宜居的城市提供科学依据。

The Heat Island Effect Response to the Urban Landscape Pattern of Haikou based on the“Source-Sink”Theory

The Landsat images of the 2000,2005,2010,2015,2018 are selected as the data source to retrieve land cover and surface temperature data.The contribution of Sink-Source landscape pattern to the heat island and its ecological effects on urban and rural gradient were analyzed by using Heat Index(HI),Sink and Source Landscape Contribution(CI_(sink),CI_(source))and Landscape Effect Index(LI)in Haikou.The results show that the heat island is concentrated on the West Coast,and in the central urban and Jiangdong New Area;the HI shows a pattern of decreasing value with the following land types:“Bare land>Artificial surface﹥Source landscape>Shrub grassland>Farmland>Sink landscape>Woodland>Water body”.In the central city section,the CI_(sink) and CI_(source) are relatively large in these five periods.The LI decreases rapidly along the urban-rural gradient,promoting the Urban Heat Island(UHI)to a large degree.In contrast,the suburban area contributes to a lesser degree.Overall,the LI fluctuates,the proportion of mitigating UHI is large,and there is a second peak outside the city center.The existing Source-Sink Landscape contributes the most to UHI in the central urban area,and this contribution decreases along the urban-rural gradient.With the continuous expansion of city-town areas,the proportion of Sink areas has increased along the gradient,and the proportion of Source areas has subsequently declined,resulting in the spatial transfer and diffusion of UHI.Therefore,a UHI mitigation strategy based on the theory of regional landscape systems is proposed here.

漳州市景观格局的热环境效应研究

城市化导致的景观格局变化是引发城市热岛效应的重要因素。深入探索景观格局的热环境效应,对保障居民健康及城市可持续发展具有重要意义。研究基于漳州市的Landsat遥感数据,运用景观生态学及空间自相关理论,揭示了景观格局与城市热环境的耦合关系。结果显示:(1)漳州市绿地、水域的热岛强度普遍较低,建设用地、耕地的热岛强度则较高。(2)景观格局与热岛强度具有较强的关联,且空间溢出效应明显。(3)绿地斑块越连续集中,其降温效果越显著;聚集或细碎的建设用地、耕地均有明显的热岛效应。研究可为应对城市气候变化、优化城市景观格局提供理论参考。

社区热岛强度空间格局及优化策略研究

城市热岛效应日益加剧,对人类可持续发展影响深远。社区是城市治理与居民生活的最主要功能单元,在社区尺度下研究热岛强度空间格局对于缓解热岛效应意义重大。以大连市中心城区为研究区,选取384个社区为基本对象,通过地表温度反演测算社区热岛强度,并以圈层划分、热点分析与景观格局指数识别城市热岛强度空间格局。结果表明中温区与低温区最大斑块值数较大,具有较高的景观优势度;高温区聚集度较高,对整体景观格局影响较大;热岛强度具有显著的空间自相关性,集聚特征明显,热岛强度冷点区具有明显的生态依附性;热岛强度由中心圈层向外呈逐级递减态势,但波动程度明显,受地形要素影响较大。研究基于热岛强度空间分布特征提出相关优化策略,为城市生态规划建设提供理性指引。

利用Landsat数据研究城市热岛效应的时空分布规律

利用收集到的2006—2020年西宁市的相关气象和遥感数据,研究西宁市地表温度、地表亮温的时空变化特征,城市热岛强度的空间分布特征呈现从城市中心向四周递减,主要是因为城区大规模人工不透水用地白天吸收大量的太阳辐射,太阳辐射直接转化为热量,因此地面温度较高,加强了热岛强度。此外,烟粉尘排放量也是城市热岛效应的重要影响因子,主要来源于道路扬尘、建筑施工扬尘、汽车尾气等,加之西宁市长年干燥,这些烟粉尘不易被带走,由于温室效应而加剧了城市热岛效应。

上海市城市热岛景观格局演变特征研究

城市热岛空间格局特征及其内在驱动机制的研究可为缓解城市热岛效应、城市规划与产业布局提供科学依据,目前这方面研究还比较少,相关机制并没有得到完全的揭示。该研究以上海市为研究对象,采用1987、1996、2002和2010年4景Landsat TM/ETM+遥感影像,对城市地表温度进行了反演与分级。借助景观格局指数,分析了上海市城市热岛景观格局时空演变特征。结果表明:随着1987-2010年上海市不断城市化,各级热岛景观类型斑块数量持续增加,高等级的城市热岛景观类型面积也持续增加,整个城市热岛景观趋于破碎化。热岛景观总体聚集度下降,连通性下降,但是低等级热岛景观向高等级热岛景观转移的面积逐渐增加,景观类型之间面积差异逐渐减小,景观均匀度和多样性增加。城市化过程中,人口数量的增加和经济的快速发展对城市热岛景观格局的形成和演变具有重要的影响。研究结果揭示了城市热岛格局随城市化进程的时空演变特征,可以为制定有效的热岛效应缓解措施提供参考依据。

城市化进程中城市热岛景观格局演变的时空特征——以厦门市为例

热岛效应作为城市化过程中产生的特有环境问题,对其形成和演变规律的研究有助于人们提出有效的应对措施。以厦门市为研究对象,利用1987—2007年等时间间隔、同时相的5景Landsat TM/ETM+遥感影像数据进行地表温度反演,在此基础上使用景观格局指数分析厦门城市热岛景观格局随城市化进程演变的趋势。结果表明:随着厦门城市化进程加深,整个热岛景观在逐渐变得更加破碎化,高等级热岛景观斑块个数、类型面积和个体面积都增大;新的高等级热岛景观斑块都出现在原有高等级斑块附近,致使高等级类型的邻近度增加而各类型之间相互接触的程度也增加;景观总体的聚合度逐渐下降,而高等级热岛景观类型的聚合度则呈上升趋势;景观水平的蔓延度总体呈下降趋势,优势度高的低等级热岛景观所占的比重下降,优势度逐渐降低;多样性指数、均匀度指数总体呈上升趋势,各热岛景观面积在各类型间的分配逐渐趋于均匀;热岛景观斑块的转化方面,在20 a间低等级斑块类型(1、2、3级)向高等级斑块类型(4、5、6级)转化的面积总体上呈增加趋势,而高等级斑块类型向低等级斑块类型转化的面积总体上呈减小趋势,且等级升高的面积明显大于同期等级降低的面积;就高等级热岛景观斑块而言,他们与3级热岛景观斑块间的相互转化最容易发生,远比高等级斑块内部各类型之间的相互转化来得容易,尤其6类和5类的转化是最为困难的热岛景观变化之一;从空间上看,各高等级热岛景观斑块都经历了数量增加、面积扩大、等级升高三个方面的变化,形成了海沧、新阳、杏林、厦门岛西北港口区和机场5个高温组团。利用景观指数分析城市热环境,可探明热岛景观随城市化演变的趋势,并为有效的热岛效应减缓措施提供直接的理论依据。

成都市城市森林格局与热岛效应的关系

城市森林对城市热岛效应有显著的缓解作用,其景观格局对热岛的分布有巨大的影响。以成都市为研究对象,采用该地区2003年的spot、landsat-7卫星影像资料,在对成都市进行城市森林景观格局的定量分析和热量反演算的基础上,结合土地利用分类图、气象观测资料、绿地统计资料,建立动态监测和空间分析模式,对城市热岛的热力分布特征和城市森林格局对热岛效应的缓解作用进行综合分析。研究结果表明:(1)成都市热量分布呈现东南多西北少的格局,这与成都市城市森林西北多东南少的格局成负相关;(2)城市绿化覆盖率越高,降温效应越明显;(3)在绿化覆盖率相当的情况下,大面积集中的绿地的降温效应明显高于面积小的绿地。基于研究结果,建议成都市在合理规划城市森林布局的同时,适当增加大面积城市森林公园的建设。