Sustainable Cities and Society最新文献_第3页

Healthy urban blue space design: Exploring the associations of blue space quality with recreational running and cycling using crowdsourced data 健康的城市蓝色空间设计：利用众包数据探索蓝色空间质量与休闲跑步和骑自行车的关系

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-22 DOI: 10.1016/j.scs.2024.105929

Urban blue space offers substantial health benefits by encouraging population physical activity. Despite much evidence on the nature-health nexus, the relationship between blue space and recreational exercises remains under-studied, limiting the realisation of health benefits in blue space design. Using crowdsourced data, including volunteered geographic information and street view image data, this study investigates the associations of blue space quality with recreational running and cycling in Rotterdam, the Netherlands. Results show that recreational exercise levels on street segments vary based on the blue space type and design. Compared to inland canals and rivers, small-scale recreational waterbodies are more conducive to running but not cycling, while both activities tend to cluster around the Nieuwe Maas River. Interestingly, the Water View Index shows a general negative association with both activities after adjusting for the blue space type. Besides the waterbody characteristics, eye-level environmental factors, including higher Green View Index, lower building density, more diverse land use, greater connected street network and fewer traffic elements, are associated with more running and cycling exercises. Results for visual complexity and neighbourhood population composition are mixed depending on the exercise type. These findings are further translated into spatial design patterns for developing exercise-supportive and health-promoting blue spaces.

城市蓝色空间通过鼓励人们进行体育锻炼而为健康带来巨大益处。尽管有很多证据表明自然与健康之间存在联系，但对蓝色空间与休闲锻炼之间关系的研究仍然不足，这限制了蓝色空间设计对健康益处的实现。本研究利用众包数据（包括自愿提供的地理信息和街景图像数据），调查了荷兰鹿特丹蓝色空间质量与休闲跑步和骑自行车之间的关系。结果表明，街道上的休闲运动水平因蓝色空间类型和设计而异。与内陆运河和河流相比，小型休闲水体更有利于跑步，但不利于骑自行车，而这两项活动往往集中在新马斯河周围。有趣的是，在对蓝色空间类型进行调整后，水景指数与这两种活动普遍呈负相关。除水体特征外，包括较高的绿色景观指数、较低的建筑密度、更多样化的土地利用、更大的街道网络连接以及较少的交通要素在内的眼观环境因素也与更多的跑步和骑自行车运动有关。视觉复杂性和社区人口构成的结果因运动类型而异。这些发现将进一步转化为空间设计模式，用于开发支持锻炼和促进健康的蓝色空间。

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引用次数: 0

Research on the mechanism and path of the coupling of digital technology and environmental regulation to promote urban green efficiency 数字技术与环境监管耦合促进城市绿色效率的机制与路径研究

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-20 DOI: 10.1016/j.scs.2024.105906

Digital technology, renowned for its embeddedness and integration, revolutionizes governance ideas, institutions, and models. Based on the panel data of 285 cities in China from 2007 to 2021, a panel vector autoregressive model (PVaR) is built to reveal the interaction mechanism between digital technology and environmental regulation. The fixed-effects panel model explored the green impact of the coupling of digital technology and environmental regulation, considering the mediating role of industrial upgrading, factor allocation, and public participation. The results show that digital technology and environmental regulation promote each other. The coupling of digital technology and environmental regulation enhances urban green efficiency, especially in economically advanced and eastern regions. Industrial upgrading, factor allocation, and public participation mediate this effect. Therefore, government departments should build ecological civilization by improving environmental management decision-making, promoting the deep integration of digital technology and environmental regulation, and exploring a new path of urban green development.

数字技术以其嵌入性和集成性著称，彻底改变了治理理念、体制和模式。基于 2007-2021 年中国 285 个城市的面板数据，建立面板向量自回归模型（PVaR），揭示数字技术与环境规制之间的互动机制。考虑到产业升级、要素配置和公众参与的中介作用，固定效应面板模型探讨了数字技术与环境规制耦合的绿色影响。结果表明，数字技术与环境监管相互促进。数字技术与环境监管的耦合提高了城市绿色效率，尤其是在经济发达地区和东部地区。产业升级、要素配置和公众参与是这一效应的中介。因此，政府部门应通过完善环境管理决策来建设生态文明，促进数字技术与环境监管的深度融合，探索城市绿色发展的新路径。

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引用次数: 0

Multi-objective energy management using a smart charging technique of a microgrid with the charging impact of plug-in hybrid electric vehicles 利用插电式混合动力电动汽车充电影响的微电网智能充电技术进行多目标能源管理

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-19 DOI: 10.1016/j.scs.2024.105923

The Microgrid (MG) concept is being developed to better integrate renewable energy sources and automate distribution networks. Microgrids combine distributed generating units (DGs) and energy storage systems to achieve this. This research paper aims to simultaneously minimize the daily operational cost and net environmental pollution of a small MG system, factoring in the charging demand from Plug-in-Hybrid Electric Vehicles (PHEVs) and consumer load demands. The proposed energy management process not only minimizes operational costs and emissions, but also determines the optimal battery size for the energy storage system. The analysis also explores the importance of two critical variables - the operation and maintenance costs of the DGs, and the total daily cost of the battery energy storage system. The demand for PHEV charging is managed using an intelligent charging approach. Given the complexity of the optimization, a recently developed metaheuristic algorithm, Slime Mould Algorithm (SMA), is applied. The performance of SMA is compared against the Grasshopper Optimization Algorithm and Sine Cosine Algorithm. To solve the multi-objective problem, a weighted sum method maintaining non-dominance and a fuzzy decision-maker technique are employed alongside the suggested algorithms. Three different scenarios verify the proposed method's effectiveness.

微电网（MG）概念的提出是为了更好地整合可再生能源并实现配电网络自动化。微电网结合了分布式发电机组（DG）和储能系统，以实现这一目标。本研究论文旨在将插电式混合动力电动汽车（PHEV）的充电需求和消费者的负载需求考虑在内，同时最大限度地降低小型 MG 系统的日常运营成本和环境净污染。所提出的能源管理流程不仅能最大限度地降低运营成本和排放，还能确定储能系统的最佳电池尺寸。分析还探讨了两个关键变量的重要性，即 DG 的运行和维护成本以及电池储能系统的每日总成本。PHEV 充电需求采用智能充电方法进行管理。考虑到优化的复杂性，采用了最近开发的一种元启发式算法--粘液模算法（SMA）。SMA 的性能与蚱蜢优化算法和正弦余弦算法进行了比较。为了解决多目标问题，除了建议的算法外，还采用了保持非优势的加权和方法和模糊决策者技术。三个不同的场景验证了建议方法的有效性。

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引用次数: 0

Study on the spatiotemporal pattern evolution of surface urban heat island in shrinking cities: Fushun and Tieling 萎缩城市地表热岛时空格局演变研究：抚顺和铁岭

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-19 DOI: 10.1016/j.scs.2024.105912

Under rapid urbanization, the urban heat island (UHI) problem impacts not only large cities, but also poses severe challenges to shrinking cities with rapidly declining population. In China, most shrinking cities are characterized by population loss alongside the expansion of built-up areas due to policy. Urban warming exacerbates the human settlement environment, with UHI intensifying due to urban expansion, while population loss simultaneously alleviates it. This raises a question: will the UHI problem be mitigated in shrinking cities? In this study, we analyze the spatiotemporal pattern evolution of surface urban heat island (SUHI) in Fushun and Tieling from 2000 to 2020 using Landsat series products. We combine landscape pattern indices and SUHI indicators, and perform correlation analyses of the factors influencing SUHI with multiscale geographically weighted regression (MGWR). The findings reveal that in Fushun, mining activities significantly impact SUHI, while in Tieling, extremely Land Surface Temperature (LST) zones are expanding and dispersing. SUHI patterns are notably shaped by subsurface conditions, and spatial configurations play key roles in regulating SUHI. However, population loss has not significantly influenced SUHI, even in shrinking cities. This study offers a new perspective for SUHI research and provides further insights into urban planning strategies.

在快速城市化进程中，城市热岛（UHI）问题不仅影响着大城市，也给人口迅速减少的萎缩城市带来了严峻挑战。在中国，大多数萎缩城市的特点是人口减少，同时由于政策原因，建成区面积扩大。城市变暖加剧了人类居住环境，城市扩张加剧了超高温影响，而人口减少同时缓解了超高温影响。这就提出了一个问题：在不断缩小的城市中，UHI 问题会得到缓解吗？在本研究中，我们利用 Landsat 系列产品分析了抚顺和铁岭 2000 年至 2020 年城市地表热岛（SUHI）的时空格局演变。我们将景观格局指数与 SUHI 指标相结合，并利用多尺度地理加权回归（MGWR）对 SUHI 的影响因素进行了相关分析。研究结果表明，在抚顺，采矿活动对 SUHI 影响显著，而在铁岭，极地表面温度（LST）区正在扩大和分散。SUHI 模式主要受地下条件影响，空间结构在调节 SUHI 方面起着关键作用。然而，人口减少并没有对 SUHI 产生明显影响，即使在不断缩小的城市中也是如此。这项研究为 SUHI 研究提供了一个新的视角，并为城市规划战略提供了进一步的见解。

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引用次数: 0

Heatwaves at work: Typology and spatial distributions of occupations exposed to heatwaves in Korea 工作场所的热浪：韩国受热浪影响职业的类型和空间分布

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-19 DOI: 10.1016/j.scs.2024.105921

Adapting to heatwaves and other climate change impacts requires identifying vulnerable demographic segments within regions. However, investigations into the spatial distribution of heatwave-vulnerable workers and its implications for local economies have been limited. This study categorizes occupations exposed to heatwaves into five subgroups and analyzes temporal changes in their spatial distributions via a spatial Markov chain model. The results indicate significant heterogeneity in vulnerability among heatwave-exposed occupations, with variations in income, foreign worker proportions, and job instability. The analysis reveals that heatwave-exposed workers are primarily concentrated outside the capital region. Group 3 (manufacturing) exhibited notable industrial clustering, whereas Group 5 (agriculture and fishery) presented high and stable concentrations in rural areas. Conversely, Group 4 (low-skilled and market-sensitive) demonstrates substantial spatial variability. Spatial Markov chain analysis highlights Group 3′s strong agglomeration tendencies influenced by neighboring cities, whereas Group 5 shows minimal spatial effects. Groups 2 and 4 experience considerable shifts in spatial distribution, with Group 2 showing only a 68.7 % probability of sustaining high concentration and Group 4 showing a 62.7 % probability. Recommendations for adaptation strategies and future research related to the economic impacts of climate change are provided on the basis of these findings.

要适应热浪和其他气候变化的影响，就必须确定区域内的弱势人口群体。然而，对易受热浪影响的工人的空间分布及其对当地经济的影响的调查还很有限。本研究将易受热浪影响的职业分为五个亚组，并通过空间马尔可夫链模型分析其空间分布的时间变化。结果表明，受热浪影响的职业在脆弱性方面存在明显的异质性，在收入、外籍工人比例和工作不稳定性方面都存在差异。分析表明，受热浪影响的工人主要集中在首都以外地区。第 3 组（制造业）表现出明显的产业集聚，而第 5 组（农业和渔业）则高度且稳定地集中在农村地区。与此相反，第 4 组（低技能和对市场敏感）显示出很大的空间变异性。空间马尔可夫链分析凸显了第 3 组受周边城市影响的强烈集聚趋势，而第 5 组的空间效应则微乎其微。第 2 组和第 4 组的空间分布发生了很大变化，第 2 组维持高度集中的概率仅为 68.7%，第 4 组为 62.7%。在这些研究结果的基础上，提出了与气候变化的经济影响有关的适应战略和未来研究建议。

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引用次数: 0

A hybrid spatiotemporal model combining graph attention network and gated recurrent unit for regional composite air pollution prediction and collaborative control 图注意网络与门控递归单元相结合的混合时空模型，用于区域复合空气污染预测与协同控制

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-19 DOI: 10.1016/j.scs.2024.105925

Machine learning (ML) models have been extensively applied in air quality prediction. However, many of these models often failed to unveil complex mechanisms and regional spatiotemporal variations of composite air pollution. This brings uncertainties in using ML models for effective composite air pollution control. The present study developed a novel hybrid spatiotemporal model framework combining Graph Attention Network (GAT) and Gated Recurrent Unit (GRU), namely the GAT-GRU model, to foresee composite air pollutions with a focus on PM_2.5 and O₃. By extracting attention matrices for PM_2.5O₃ composite pollution and applying the Louvain algorithm, the framework established effective community network divisions for coordinated control of PM_2.5O₃ composite pollution. The framework was applied and tested in China's “2 + 26″ cities, a city cluster with most heavy PM_2.5 and O₃ pollution and precursor emission sources. The results demonstrate that the framework successfully captured spatiotemporal evolution of combined PM_2.5 and O₃ pollution. The attention matrix is autonomously generated during course of the model learning process with the aim to interpret the complex interactions among “2 + 26″ cities. The framework provides a new perspective for the interpretability of artificial intelligence models and offers a methodological support and scientific evidence for formulating regional pollution cooperative governance strategies.

机器学习（ML）模型已被广泛应用于空气质量预测。然而，其中许多模型往往无法揭示复合空气污染的复杂机制和区域时空变化。这给使用 ML 模型有效控制复合空气污染带来了不确定性。本研究开发了一种新颖的混合时空模型框架，即 GAT-GRU 模型，该框架结合了图形注意力网络（GAT）和门控循环单元（GRU），用于预测以 PM2.5 和 O3 为重点的复合空气污染。通过提取 PM2.5O3 复合污染的注意力矩阵并应用卢万算法，该框架建立了有效的社区网络划分，以协调控制 PM2.5O3 复合污染。该框架在中国 "2+26 "城市（PM2.5 和 O3 污染最严重、前体排放源最多的城市群）中进行了应用和测试。结果表明，该框架成功捕捉了 PM2.5 和 O3 综合污染的时空演变。注意矩阵是在模型学习过程中自主生成的，目的是解释 "2 + 26 "城市之间复杂的相互作用。该框架为人工智能模型的可解释性提供了新的视角，为制定区域污染合作治理战略提供了方法论支持和科学依据。

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引用次数: 0

Analysis of the spatial characteristics and driving forces of underground consumer service space in Chinese megacities based on multi-source data 基于多源数据的中国特大城市地下消费服务空间特征及驱动力分析

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-18 DOI: 10.1016/j.scs.2024.105924

Underground consumer service spaces (UCSS) offer new solutions for urban residents’ daily needs, but existing studies on their distribution and driving forces are often fragmented and overshadowed by research on other underground spaces, lacking targeted analysis. This study examines UCSS in the central urban areas of seven representative Chinese megacities. Using spatial analysis methods like kernel density estimation, multi-distance spatial clustering, and geographical detectors, the spatial characteristics and driving forces of UCSS are analyzed alongside aboveground consumer service spaces (ACSS). Results show that both ACSS and UCSS exhibit multi-centered, concentric spatial patterns, though UCSS demonstrates higher spatial aggregation. Unlike other underground public spaces (UPS), UCSS relies more on service industry agglomeration and market factors, while other UPS are more influenced by surrounding development intensity. UCSS follows the core principles of central place theory but deviates from the market-driven patterns typical of ACSS. Socioeconomic conditions and transportation infrastructure form the foundational basis for UCSS distribution, while service industry agglomeration, market dependence, and land development intensity exert more direct influence. The commercial atmosphere and existing underground space development play critical roles in UCSS distribution. Two key spatial scales for understanding UCSS distribution are the strong influence zones of shopping malls and metro stations, and high-density urban areas.

地下消费服务空间（UCSS）为城市居民的日常需求提供了新的解决方案，但现有关于其分布和驱动力的研究往往比较零散，且被其他地下空间的研究所掩盖，缺乏有针对性的分析。本研究考察了中国七个具有代表性的特大城市中心城区的地下空间。利用核密度估计、多距离空间聚类和地理探测器等空间分析方法，分析了地下综合服务空间与地上消费服务空间（ACSS）的空间特征和驱动力。结果表明，ACSS 和 UCSS 都表现出多中心同心空间模式，但 UCSS 表现出更高的空间聚集性。与其他地下公共空间（UPS）不同，UCSS 更多地依赖于服务业集聚和市场因素，而其他地下公共空间则更多地受到周边开发强度的影响。UCSS 遵循中心地理论的核心原则，但偏离了 ACSS 典型的市场驱动模式。社会经济条件和交通基础设施是 UCSS 分布的基础，而服务业集聚、市场依赖和土地开发强度则对其产生更直接的影响。商业氛围和现有的地下空间开发对 UCSS 的分布起着至关重要的作用。了解 UCSS 分布的两个关键空间尺度是购物中心和地铁站的强影响区以及高密度城区。

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引用次数: 0

Green space-building integration for Urban Heat Island mitigation: Insights from Beijing's fifth ring road district 缓解城市热岛的绿色空间建筑一体化：北京五环路地区的启示

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-18 DOI: 10.1016/j.scs.2024.105917

In this research, we delve into the complex arrangement of urban landscapes, where green spaces and buildings are not merely co-existing but are interwoven into a cohesive fabric that shapes the thermal environment. Our approach transcends the conventional methods of analysis, which typically isolate the roles of greenery or built environments. Instead, we adopt a synergistic perspective that recognizes the collective influence of these landscape constituents on the urban thermal pattern. Key insights are: (1) A linear decrease in average land surface temperature with increasing green space coverage is observed. However, substantial temperature variations (up to 8 °C) within the same coverage interval highlight the significant impact of built-up pattern on thermal conditions; (2) High Building Height and Floor Area Ratio, and low Building Coverage Ratio and Sky View Factor, are linked to cooler temperatures in areas with up to 50 % green space; (3) The study suggests that low-temperature areas can inform the adjustment of built-up patterns in high-temperature areas, offering a strategy for thermal environment optimization within specific green space coverage intervals. This research contributes insights into the integrated planning of green spaces and buildings, with implications for urban development and renewal initiatives aiming to enhance the urban thermal environment.

在这项研究中，我们深入探讨了城市景观的复杂布局，绿地与建筑不仅仅是共存的关系，而是交织在一起，形成了一个塑造热环境的整体结构。我们的研究方法超越了传统的分析方法，这种方法通常将绿化或建筑环境的作用孤立开来。相反，我们采用了一种协同视角，认识到这些景观成分对城市热模式的集体影响。主要观点如下(1) 随着绿地覆盖率的增加，地表平均温度呈线性下降。然而，在同一覆盖区间内，温度变化很大（最高达 8 °C），这凸显了建筑形态对热环境的重要影响；（2）在绿地率高达 50% 的地区，高建筑高度和容积率、低建筑覆盖率和天空视角系数与较低的温度相关；（3）研究表明，低温地区可以为高温地区建筑形态的调整提供参考，从而为特定绿地覆盖区间内的热环境优化提供策略。这项研究为绿地和建筑的综合规划提供了启示，对旨在改善城市热环境的城市发展和更新计划具有重要意义。

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引用次数: 0

Spatial optimization of land use and carbon storage prediction in urban agglomerations under climate change: Different scenarios and multiscale perspectives of CMIP6 气候变化下城市群土地利用和碳储存的空间优化预测：CMIP6 的不同情景和多尺度视角

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-18 DOI: 10.1016/j.scs.2024.105920

Land use/land cover (LULC) structure optimization can effectively increase carbon storage/carbon sequestration (CS) and help realize carbon neutrality goals¹. Studying the spatial distributions of LULC and CS under climate change conditions is highly important for realizing sustainable development goals. This study is based on different climate change models, and the coordinated development of economic, water, carbon and ecological sustainability was considered to establish a comprehensive multiscale, multiscenario and multiobjective LULC optimization model. Then, different climate change scenarios were optimized, and regional CS values were predicted. The LULC simulation model provided satisfactory simulation results at different scales. Notably, the average accuracy exceeded 0.92. The optimized land expansion results exhibited heterogeneity. Forestland change accounted for the largest proportion of the total LULC change. After optimization, the CS values under the different scenarios were similar. The northwestern part of the study area served as the main carbon sink area. The aim of this study was to respond to future complex climate change by rationally planning the LULC structure, thus achieving the sustainable development of urban agglomerations.

优化土地利用/土地覆盖（LULC）结构可有效增加碳储存/碳固存（CS），有助于实现碳中和目标1。研究气候变化条件下 LULC 和 CS 的空间分布对实现可持续发展目标非常重要。本研究基于不同的气候变化模型，考虑经济、水、碳和生态可持续性的协调发展，建立了多尺度、多情景、多目标的 LULC 综合优化模型。然后，对不同的气候变化情景进行了优化，并预测了区域 CS 值。LULC 模拟模型在不同尺度上都取得了令人满意的模拟结果。值得注意的是，平均精度超过了 0.92。优化后的土地扩展结果呈现出异质性。林地变化在 LULC 总变化中所占比例最大。优化后，不同方案下的 CS 值相近。研究区域的西北部是主要的碳汇区。本研究旨在通过合理规划 LULC 结构来应对未来复杂的气候变化，从而实现城市群的可持续发展。

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引用次数: 0

Tracking the impact of the land cover change on the spatial-temporal distribution of the thermal comfort: Insights from the Qinhuai River Basin, China 跟踪土地覆被变化对热舒适度时空分布的影响：中国秦淮河流域的启示

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-10-18 DOI: 10.1016/j.scs.2024.105916

China's rapid economic growth and urbanization have caused significant Land Cover Changes (LCC), worsened the Urban Heat Island (UHI) effect and reducing the Thermal Comfort (TC). Despite existing studies, there remains a gap in understanding the specific contributions of various LCC types to the TC, particularly in Qinhuai River Basin. This study addresses this gap by examining the LCC effects from 2013 to 2022 based on targeted metrics. We propose a novel TC classification model and introduce indices, including the Land Cover Contribution Index (LCI) and the Land Cover Classification Contribution Index (LCCI), to quantify the influence of different LCC types on the TC. Our findings reveal that farmland and woodland positively impact the TC, while the negative influence of impervious surfaces has intensified. The area of farmland in the most comfortable category has shown significant variability, while impermeable surfaces in uncomfortable and very uncomfortable categories have surged. Additionally, the Urban Water Body Contribution Index (U-WCI) consistently exceeded the Non-Urban Water Body Contribution Index (N-WCI), indicating an enhanced UHI effect within urban areas. This study concludes that changes in farmland and impervious surfaces are crucial for the TC and provides practical recommendations for land use planning against climate change.

中国经济的快速增长和城市化进程引起了显著的土地覆被变化（LCC），加剧了城市热岛效应（UHI），降低了热舒适度（TC）。尽管已有相关研究，但在了解各种土地覆被类型对热舒适度的具体贡献方面仍存在差距，尤其是在秦淮河流域。本研究通过研究 2013 年至 2022 年基于目标指标的 LCC 效应来填补这一空白。我们提出了一种新的热量传输分类模型，并引入了土地覆被贡献指数（LCI）和土地覆被分类贡献指数（LCCI）等指数来量化不同土地覆被类型对热量传输的影响。我们的研究结果表明，农田和林地对 TC 有正面影响，而不透水地面的负面影响则有所加剧。最舒适类别中的农田面积变化很大，而不舒适和非常不舒适类别中的不透水表面面积则激增。此外，城市水体贡献指数（U-WCI）一直超过非城市水体贡献指数（N-WCI），表明城市地区的 UHI 效应增强。本研究的结论是，农田和不透水表面的变化对热带气旋至关重要，并为应对气候变化的土地利用规划提供了实用建议。

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引用次数: 0