Data in Brief最新文献_第5页

UAV-LiDAR dataset of Pangandaran coastal tourism hotspots for tsunami and climate risk valuation and exposure mapping Pangandaran沿海旅游热点地区的无人机-激光雷达数据集，用于海啸和气候风险评估和暴露测绘。

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-24 DOI: 10.1016/j.dib.2026.112505

Mega Laksmini Syamsuddin , Umar Abdurrahman , Ajeng Riska Puspita , Sunarto , Qurnia Wulan Sari , Fadli Syamsudin , Indrawan Fadhil Pratyaksa , Iqbal Maulana Cipta , Ivonne Milichristi Radjawane , Hansan Park

This article presents a high-resolution UAV–LiDAR dataset acquired over the main coastal tourism hotspots of Pangandaran, West Java, Indonesia (WGS84 / UTM Zone 49S). The survey was conducted using a DJI Matrice 300 RTK equipped with a CHCNAV AA450 LiDAR system at altitudes of 77–83 m AGL, following grid-based flight lines with 80% forward and 70% side overlap. The final point cloud, delivered in LAS format, exhibits a mean density of approximately 865 pts/m², with dominant values of 600–800 pts/m² across roads, roofs, and open terrain, and localized peaks exceeding 3,000 pts/m² in areas of flight-line overlap. Ground control was established using three static base stations, with 14 calibration control points and 8 independent validation check points. Accuracy assessment yields RMSE values of 0.072 m (Easting), 0.062 m (Northing), and 0.138 m (Elevation), with corresponding mean biases of 0.017 m, 0.017 m, and 0.044 m, confirming centimeter-level positional precision suitable for detailed coastal mapping. The dataset includes DSM and DTM derivatives, block-based tiles, metadata, and processing reports, supporting its use in tsunami exposure assessment, climate-risk valuation, urban coastal planning, and remote-sensing education. As one of the first openly accessible UAV–LiDAR datasets for an Indonesian coastal tourism hotspot, it provides a reproducible, high-density 3D resource for research, hazard analysis, and sustainable coastal development.

本文介绍了在印度尼西亚西爪哇邦干达兰主要沿海旅游热点（WGS84 / UTM区49S）获取的高分辨率无人机-激光雷达数据集。该调查使用了一架配备CHCNAV AA450激光雷达系统的大疆矩阵300 RTK飞机，飞行高度为77-83米，飞行高度为80%向前重叠，70%侧面重叠。最终的点云以LAS格式交付，其平均密度约为865 pts/m²，在道路、屋顶和开阔地形上的主要值为600-800 pts/m²，在航线重叠区域的局部峰值超过3,000 pts/m²。地面控制采用3个静态基站，14个校准控制点和8个独立验证检查点。精度评估的RMSE值分别为0.072 m （east）、0.062 m （north）和0.138 m (Elevation)，相应的平均偏差分别为0.017 m、0.017 m和0.044 m，确定了适合沿海详细制图的厘米级定位精度。该数据集包括DSM和DTM衍生产品、基于块的瓦片、元数据和处理报告，支持其在海啸暴露评估、气候风险评估、城市沿海规划和遥感教育中的应用。作为印尼沿海旅游热点地区首批可公开访问的无人机-激光雷达数据集之一，它为研究、危害分析和沿海可持续发展提供了可复制的高密度3D资源。

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引用次数: 0

Genome data of Propionibacterium freudenreichii J117, a functional strain from raw-milk cheese 原乳奶酪功能菌株弗氏丙酸杆菌J117的基因组数据。

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-24 DOI: 10.1016/j.dib.2026.112498

Paulina Deptula , Jenni Sihvola , Pekka Varmanen

This dataset reports the complete genome sequence of Propionibacterium freudenreichii strain J117, a food-grade bacterium isolated from Austrian Vorarlberger Bergkäs cheese. The strain was selected for its application in a co-fermentation platform aimed at enhancing vitamin B12 content in plant-based fermented foods. Genomic DNA was extracted from anaerobic cultures grown in yeast extract lactate (YEL) broth and sequenced using PacBio Sequel II long-read technology with SMRT Cell 8 M. High-fidelity (HiFi) reads were generated, and circular consensus sequences (CCS) were assembled using the Improved Phased Assembler (IPA v2).

Genome annotation was performed with Bakta v1.10.4. Antibiotic resistance screening was carried out using the Resistance Gene Identifier (RGI v6.0.3) from the Comprehensive Antibiotic Resistance Database (CARD) via the PROKSEE platform. No plasmid-encoded resistance determinants were identified. The genome comprises two circular replicons and includes full annotation of coding sequences, RNAs, CRISPR array, and pseudogenes.

The raw sequencing data, genome assembly files, and annotation outputs are included in the associated data repository, organized in subfolders for raw reads, assemblies, and analysis results. This dataset supports the related research article: Zhang, R., Chen, L., Zhang, D., Sihvola, J., Chamlagain, B., Olin, M., Piironen, V., & Varmanen, P. Innovative co-fermentation of Propionibacterium freudenreichii and Rhizopus oryzae enhances vitamin B12, riboflavin, and flavor profile components in sweet fermented glutinous rice. Food Chemistry, 503 (2026).

The availability of this genome provides a reference for comparative genomic analysis, functional pathway prediction, and strain development. It also facilitates safety assessment of food-related strains, such as the absence of mobile antibiotic resistance genes, thereby supporting the transparent use of J117 in fermented food applications.

该数据集报道了从奥地利Vorarlberger Bergkäs奶酪中分离出的一种食品级细菌——弗氏丙酸杆菌J117菌株的完整基因组序列。选择该菌株用于旨在提高植物性发酵食品中维生素B12含量的共发酵平台。从酵母提取物乳酸（YEL）培养液中厌氧培养物中提取基因组DNA，使用PacBio Sequel II长读技术与SMRT Cell 8 m进行测序，生成高保真（HiFi）读段，并使用改进的分阶段组装器（IPA v2）组装环状一致序列（CCS）。使用Bakta v1.10.4进行基因组注释。通过PROKSEE平台，使用抗生素耐药综合数据库（CARD）中的耐药基因标识符（RGI v6.0.3）进行抗生素耐药筛选。未发现质粒编码的抗性决定因素。基因组由两个圆形复制子组成，包括编码序列、rna、CRISPR阵列和假基因的完整注释。原始测序数据、基因组组装文件和注释输出包含在关联的数据存储库中，并组织在用于原始读取、组装和分析结果的子文件夹中。该数据集支持相关研究文章：Zhang， R., Chen， L., Zhang， D., Sihvola， J., Chamlagain， B., Olin， M., Piironen， V., Varmanen， P.，创新的弗氏丙酸杆菌和米根霉共发酵提高了甜发酵糯中的维生素B12、核黄素和风味成分。食品化学，2003,26(3):326 - 326。该基因组的可用性为比较基因组分析、功能途径预测和菌株开发提供了参考。它还有助于食品相关菌株的安全评估，例如不存在流动抗生素耐药基因，从而支持J117在发酵食品应用中的透明使用。

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引用次数: 0

A dataset for forty complete bacterial genome sequences in cultures of the toxic dinoflagellate Ostreopsis cf. ovata 四十完整的细菌基因组序列的数据集，在培养有毒鞭毛藻Ostreopsis c.f ovata

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-23 DOI: 10.1016/j.dib.2026.112499

Yuki Yoshioka , Chika Ando , Hiroshi Yamashita , Mayumi Kawamitsu , Masanobu Kawachi , Yuta Tsunematsu , Eiichi Shoguchi

Increasing occurrences of toxic dinoflagellate blooms are a growing concern under climate change. The benthic dinoflagellate Ostreopsis blooms through mechanisms that remain poorly understood and is assumed to produce palytoxin-like compounds such as ovatoxins. Recent studies have highlighted the diversity of bacterial communities associated with Ostreopsis and suggested a possible role for these bacteria in toxin biosynthesis. However, genome information on potential bacterial toxin producers remains limited. Here, we report a dataset of bacterial metagenome-assembled genomes (MAGs) obtained from the culture of the toxic dinoflagellate Ostreopsis cf. ovata strain (NIES-3351). HiFi long reads from PacBio Revio system were assembled with hifiasm-meta. We identified forty complete bacterial MAGs, each with an estimated completeness of 93-100%. These MAGs span a wide range of genome sizes (1.5 Mb to 6.7 Mb) and GC contents (36% to 67%). The dataset is available at DDBJ/ENA/GenBank under accession number PRJDB37958.

在气候变化的影响下，越来越多的有毒鞭毛藻爆发引起了人们的关注。底栖鞭毛藻Ostreopsis的繁殖机制尚不清楚，它被认为会产生类似于palytoxin的化合物，如卵细胞毒素。最近的研究强调了与Ostreopsis相关的细菌群落的多样性，并提出了这些细菌在毒素生物合成中的可能作用。然而，关于潜在细菌毒素产生者的基因组信息仍然有限。在这里，我们报告了从有毒鞭毛藻Ostreopsis cfv . ovata菌株（ies -3351）培养中获得的细菌元基因组组装基因组（MAGs）数据集。用hifiasm-meta对PacBio Revio系统的HiFi长读数进行组装。我们鉴定了40个完整的细菌MAGs，每个MAGs的完整性估计为93-100%。这些mag跨越了广泛的基因组大小（1.5 Mb至6.7 Mb）和GC含量（36%至67%）。该数据集可在DDBJ/ENA/GenBank上获得，登录号为PRJDB37958。

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引用次数: 0

A human fecal metaproteomic dataset from celiac disease patients on gluten-free diet with or without poly-autoimmunity 来自无麸质饮食的乳糜泻患者的粪便蛋白质组学数据集，有或没有多重自身免疫

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-22 DOI: 10.1016/j.dib.2026.112501

Marcello Abbondio , Alessandro Tanca , Rosangela Sau , Giovanna Pira , Alessandra Errigo , Roberto Manetti , Giovanni Mario Pes , Stefano Bibbò , Maria Pina Dore , Sergio Uzzau

This dataset provides the fecal metaproteome profiles of 28 celiac disease patients on a gluten-free diet, distinguished by the presence or absence of co-occurring autoimmune conditions. The resource includes raw liquid chromatography-tandem mass spectrometry (LC-MS/MS) files, database search results, protein/peptide identification outputs, and taxonomic/functional annotation outputs, along with comprehensive anthropometric, clinical, and dietary metadata for each patient. The identified proteins originate from microbial, human, and plant sources, consistent with the multi-database search strategy used. This collection is designed for reuse in meta-analyses and integrative studies exploring functional changes in the gut microbiome related to auto-immune status and dietary variables. The complete dataset is available via the ProteomeXchange Consortium with the identifier PXD069517.

该数据集提供了28例无麸质饮食的乳糜泻患者的粪便元蛋白质组谱，通过存在或不存在共同发生的自身免疫性疾病来区分。该资源包括原始的液相色谱-串联质谱（LC-MS/MS）文件、数据库搜索结果、蛋白质/肽鉴定输出和分类/功能注释输出，以及每个患者的综合人体测量学、临床和饮食元数据。鉴定的蛋白质来源于微生物、人类和植物，与使用的多数据库搜索策略一致。该收集旨在用于荟萃分析和综合研究，探索与自身免疫状态和饮食变量相关的肠道微生物组的功能变化。完整的数据集可通过ProteomeXchange Consortium获得，标识符为PXD069517。

引用次数: 0

PhenoStras2022: A 2022 smartphone-based image and field phenology dataset for monitoring urban trees in Strasbourg, France PhenoStras2022: 2022年基于智能手机的图像和实地物候数据集，用于监测法国斯特拉斯堡的城市树木

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-22 DOI: 10.1016/j.dib.2026.112502

Clément Bressant , Pierre-Alexis Herrault , Anne Puissant

Urban trees provide critical ecosystem services but remain vulnerable to climate change and urban environmental stresses. To improve understanding of their phenological dynamics and support reproducible urban vegetation monitoring, PhenoStras2022 is introduced, a dataset based on non-destructive, low-cost (using a portable smartphone-based setup) ground-based observations. Data were collected throughout a complete phenological cycle in 2022 across 40 green sites in Strasbourg, France. Two types of photographic acquisitions were conducted: Digital Hemispherical Photography (DHP) and Front-View Photography (FVP), complemented by field-based phenological observations following a simplified BBCH scale. The dataset is organized to enable a range of applications, including remote sensing products validation and urban climate studies. PhenoStras2022 addresses the current lack of ground-based urban phenology data and provides a robust foundation for analysing seasonal patterns and the resilience of urban trees. It also promotes participatory science by offering an accessible, replicable acquisition protocol, contributing to the strengthening of phenological monitoring networks in the context of a changing climate.

城市树木提供重要的生态系统服务，但仍然容易受到气候变化和城市环境压力的影响。为了提高对其物候动态的理解并支持可重复的城市植被监测，引入了PhenoStras2022，这是一个基于非破坏性、低成本（使用便携式智能手机设置）地面观测的数据集。研究人员于2022年在法国斯特拉斯堡的40个绿色地点收集了完整的物候周期数据。进行了两种类型的摄影采集：数字半球摄影（DHP）和前视图摄影（FVP），并根据简化的BBCH量表进行实地物候观察。该数据集的组织是为了实现一系列应用，包括遥感产品验证和城市气候研究。PhenoStras2022解决了目前缺乏地面城市物候数据的问题，为分析季节模式和城市树木的恢复力提供了坚实的基础。它还通过提供可获取、可复制的采集方案来促进参与性科学，有助于在气候变化的背景下加强物候监测网络。

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引用次数: 0

BrinjalFruitX: A field-collected image dataset for machine learning and deep learning-based disease identification in brinjal fruits BrinjalFruitX：用于机器学习和基于深度学习的茄子果实疾病识别的现场采集图像数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-21 DOI: 10.1016/j.dib.2026.112490

Abu Kowshir Bitto , Md. Zahid Hasan , Md. Hasan Imam Bijoy , Khalid Been Badruzzaman Biplob , Mohammad Mahadi Hassan , Mohammad Shohel Rana , Abdul Kadar Muhammad Masum

Brinjal (Solanum melongena) or eggplant is one of the four most essential vegetable crops that are grown in Bangladesh and contribute significantly to the agricultural industry of the country. Brinjal supports the livelihood of numerous small farmers; however, brinjal is severely susceptible to various fruit diseases, which have serious impacts on yield quality and may cause considerable economic losses. While most existing plant disease datasets primarily focus on leaf-related disorders, only a limited number include fruit-related diseases and even those contain very few classes. This gap is significant because fruit diseases directly affect crop quality, market value, and overall yield. This is why we present here a new and comprehensive dataset that is unparalleled, exclusively for brinjal fruit diseases. This data set consists of 1823 high-quality, labelled images, across five distinct classes: Phomopsis Blight, Shoot and Fruit Borer, Fruit Cracking, Wet Rot, and Healthy Fruit. The images were collected from real farm conditions in numerous areas of Bangladesh to ensure a robust sample of varied environmental and farming practices impacting the growth of diseases. This dataset is designed with the unique aim to support plant disease research and enhance training of deep learning models for autonomous disease detection. Lastly, the dataset will allow early disease detection, enhancing crop management practice, reduction of losses, and increasing farmers' economic returns. The release of this dataset will encourage agricultural research as well as practical use in precision agriculture.

茄子（茄）或茄子是孟加拉国种植的四种最重要的蔬菜作物之一，对该国的农业作出了重大贡献。茄子支撑着无数小农的生计；然而，茄子极易发生各种果实病害，严重影响产量品质，并可能造成巨大的经济损失。虽然大多数现有的植物疾病数据集主要关注与叶片相关的疾病，但只有有限数量的数据集包括与水果相关的疾病，甚至这些疾病包含的类别也很少。这一差距是显著的，因为水果病害直接影响作物品质、市场价值和总产量。这就是为什么我们在这里提出一个新的和全面的数据集，是无与伦比的，专门为茄子果实疾病。该数据集由1823张高质量的、带标签的图像组成，分为五个不同的类别：油菜枯萎病、茎和果实蛀虫、果实开裂、湿腐病和健康水果。这些图像是从孟加拉国许多地区的真实农场条件中收集的，以确保对影响疾病增长的各种环境和农业做法提供可靠的样本。该数据集的设计具有独特的目的，以支持植物病害研究和增强深度学习模型的训练，用于自主病害检测。最后，该数据集将有助于早期发现疾病，加强作物管理实践，减少损失，并提高农民的经济回报。该数据集的发布将鼓励农业研究以及精准农业的实际应用。

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引用次数: 0

Monitoring ecosystem functions in mountain catchments of chilean patagonia: A cluster-based dataset 智利巴塔哥尼亚山区集水区生态系统功能监测：基于集群的数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-21 DOI: 10.1016/j.dib.2026.112481

Paulo Moreno-Meynard

This dataset documents the spatially explicit quantification of multiple ecosystem functions across 12 mountain headwater catchments in the Aysén Region of Chilean Patagonia. Designed to capture landscape variability, the observational framework employs a paired-catchment approach, comparing basins with different degrees of anthropogenic disturbance across two forest types: deciduous and evergreen. Each catchment is treated as an integrated landscape unit, with cluster-based field measurements capturing fine-scale variation in vegetation structure, biomass, soil conditions, and species richness.

The field inventory integrates and adapts methodologies from several national and international forest monitoring frameworks. Its core structure is based on Chile’s Continuous National Forest Inventory, but also incorporates sampling concepts and measurement protocols inspired by the Swiss National Forest Inventory (LFI), the U.S. Forest Inventory and Analysis (FIA) program, and long-term ecological monitoring plots used in New Zealand. This hybrid design ensures multidimensional assessment of ecosystem functions while enhancing cross-regional comparability.

The sampling design addresses ecosystem functions across four service categories: provisioning (sawlog and firewood volume), regulating (carbon stocks in trees, shrubs, and deadwood, and decadal sequestration rates), supporting (soil formation and erosion proxies, plus nutrient concentrations), and biodiversity maintenance (vascular plant and epiphyte).

This dataset supports ecological synthesis, spatial modeling, and integration into broader assessments of ecosystem services and land-use impacts under changing environmental conditions.

该数据集记录了智利巴塔哥尼亚ayssamn地区12个山区水源集水区多种生态系统功能的空间明确量化。为了捕捉景观变化，该观测框架采用了配对集水区方法，比较了两种森林类型（落叶森林和常绿森林）中不同程度人为干扰的流域。每个集水区都被视为一个完整的景观单元，通过基于集群的实地测量捕获植被结构、生物量、土壤条件和物种丰富度的细微变化。实地清查综合并调整了若干国家和国际森林监测框架的方法。其核心结构以智利的连续国家森林清查为基础，但也结合了瑞士国家森林清查（LFI）、美国森林清查和分析（FIA）计划以及新西兰使用的长期生态监测地块所启发的抽样概念和测量方案。这种混合设计确保了生态系统功能的多维评估，同时增强了跨区域的可比性。采样设计涉及四个服务类别的生态系统功能：供应（锯材和木柴量），调节（树木、灌木和枯木的碳储量，以及年代际封存率），支持（土壤形成和侵蚀代理，以及养分浓度），以及维持生物多样性（维管植物和附生植物）。该数据集支持生态综合、空间建模，并整合到不断变化的环境条件下更广泛的生态系统服务和土地利用影响评估中。

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引用次数: 0

Dataset for drone problem identification and severity estimation 用于无人机问题识别和严重性估计的数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-21 DOI: 10.1016/j.dib.2026.112494

Swardiantara Silalahi, Tohari Ahmad, Hudan Studiawan

The paper proposes DroSev, a dataset for drone problem identification and severity estimation. The collection of drone flight log messages was acquired from publicly accessible sources on Mendeley Data and AirData. This dataset consists of two subtasks: binary problem identification and multiclass problem severity classification. The former task used only the collection of log messages from Mendeley Data, and the latter task used the merged collection of log messages from both sources. Each subtask has a train and test split with an 80:20 ratio generated with stratified sampling. Further syntactical characteristics are reported and summarized.

本文提出了用于无人机问题识别和严重性估计的数据集DroSev。无人机飞行日志信息的收集是从Mendeley Data和AirData的公开来源获得的。该数据集包括两个子任务：二元问题识别和多类问题严重性分类。前一个任务仅使用来自Mendeley Data的日志消息集合，后一个任务使用来自两个源的日志消息合并集合。每个子任务都有一个训练和测试分割，分层抽样生成的比例为80:20。进一步的语法特征进行了报道和总结。

引用次数: 0

C3I-SynMicrosaccade: A pipeline and dataset for microsaccade recognition using neuromorphic event camera streams C3I-SynMicrosaccade：使用神经形态事件相机流进行微跳识别的管道和数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-21 DOI: 10.1016/j.dib.2026.112491

Waseem Shariff , Timothy Hanley , Maciej Stec , Hossein Javidnia , Peter Corcoran

This article presents a C3I-SynMicrosaccade dataset: a synthetic microsaccade dataset designed to enable event-based modelling and classification of microsaccadic eye movements. Using Blender, we generated high-resolution RGB sequences of microsaccades, characterized by small, transient eye rotations around a fixed head pose. Each microsaccade follows a horizontal-boomerang-like trajectory, simulating the natural back-and-forth displacement of the eye during visual fixation. Seven distinct angular classes, ranging from 0.5° to 2.0°, capture varying motion amplitudes while maintaining consistent scene, lighting, and texture conditions. The rendered RGB frames were converted into event-based data streams using the v2e simulator, which replicates the asynchronous behaviour of neuromorphic vision sensors. Temporal durations and event counts were carefully controlled and resampled to ensure class balance and eliminate bias toward motion magnitude. The resulting dataset comprises 175,000 event sequences (87,500 per eye), providing a large-scale, balanced foundation for microsaccade recognition, neuromorphic vision research, and synthetic-to-real transfer learning. This work offers a controlled, reproducible framework for studying fixational eye movements and evaluating event-based algorithms under fine motion dynamics.

本文介绍了一个C3I-SynMicrosaccade数据集：一个合成的微跳数据集，旨在实现基于事件的微跳眼运动建模和分类。使用Blender，我们生成了高分辨率的RGB微扫视序列，其特征是围绕固定的头部姿势进行小而短暂的眼睛旋转。每个微跳都遵循水平回飞镖般的轨迹，模拟眼睛在视觉固定期间自然的前后位移。七个不同的角度类别，范围从0.5°到2.0°，捕捉不同的运动幅度，同时保持一致的场景，照明和纹理条件。使用v2e模拟器将渲染的RGB帧转换为基于事件的数据流，该模拟器复制了神经形态视觉传感器的异步行为。时间持续时间和事件计数被仔细控制和重新采样，以确保类平衡和消除对运动大小的偏见。结果数据集包括175,000个事件序列（每只眼睛87,500个），为微跳频识别、神经形态视觉研究和合成到真实的迁移学习提供了大规模、平衡的基础。这项工作提供了一个可控的、可重复的框架，用于研究注视眼运动和评估精细运动动力学下基于事件的算法。

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引用次数: 0

100 m climate and heat stress data up to 2100 for 142 cities around the globe 截至2100年全球142个城市的100米气候和热应力数据

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief

Pub Date : 2026-01-21 DOI: 10.1016/j.dib.2026.112497

Niels Souverijns , Dirk Lauwaet , Quentin Lejeune , Chahan M. Kropf , Kam Lam Yeung , Shruti Nath , Carl F. Schleussner

Cities worldwide are increasingly facing the challenges of heat stress, a problem expected to worsen with ongoing climate change. The lack of detailed, city-specific data hinders effective response measures and limits the adaptive capacity of urban populations. In this data descriptor, we introduce a comprehensive database providing climate and heat stress information for 142 cities globally, covering the present and extending projections up to 2100 across three distinct climate scenarios, including two overshoot scenarios. This dataset includes 34 heat stress indicators at a spatial resolution of 100 meters, offering a unique database to identify vulnerable areas and deepen the understanding of urban heat risks. The data is presented through an accessible, user-friendly dashboard, enabling policymakers, researchers, and city planners, as well as non-experts, to easily visualise and interpret the findings, supporting more informed decision-making and urban adaptation strategies.

世界各地的城市正日益面临热应激的挑战，随着气候的持续变化，这一问题预计会恶化。缺乏具体城市的详细数据妨碍了有效的应对措施，限制了城市人口的适应能力。在这一数据描述中，我们介绍了一个综合数据库，提供了全球142个城市的气候和热应力信息，涵盖了目前和延伸到2100年的三种不同气候情景，包括两种超调情景。该数据集包括34个空间分辨率为100米的热应力指标，为识别脆弱区域和加深对城市热风险的理解提供了独特的数据库。数据通过易于访问、用户友好的仪表板呈现，使政策制定者、研究人员和城市规划者以及非专家能够轻松地可视化和解释调查结果，从而支持更明智的决策和城市适应战略。

引用次数: 0