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A Spatial Case-Based Reasoning Method for Healthy City Assessment: A Case Study of Middle Layer Super Output Areas (MSOAs) in Birmingham, England 健康城市评估的空间案例推理方法:英国伯明翰中层高产出区(MSOA)案例研究
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-31 DOI: 10.3390/ijgi13080271
Shuguang Deng, Wei Liu, Ying Peng, Binglin Liu
Assessing healthy cities is a crucial strategy for realizing the concept of “health in all policies”. However, most current quantitative assessment methods for healthy cities are predominantly city-level and often overlook intra-urban evaluations. Building on the concept of geographic spatial case-based reasoning (CBR), we present an innovative healthy city spatial case-based reasoning (HCSCBR) model. This model comprehensively integrates spatial relationships and attribute characteristics that impact urban health. We conducted experiments using a detailed multi-source dataset of health environment determinants for middle-layer super output areas (MSOAs) in Birmingham, England. The results demonstrate that our method surpasses traditional data mining techniques in classification performance, offering greater accuracy and efficiency than conventional CBR models. The flexibility of this method permits its application not only in intra-city health evaluations but also in extending to inter-city assessments. Our research concludes that the HCSCBR model significantly improves the precision and reliability of healthy city assessments by incorporating spatial relationships. Additionally, the model’s adaptability and efficiency render it a valuable tool for urban planners and public health researchers. Future research will focus on integrating the temporal dimension to further enhance and refine the healthy city evaluation model, thereby increasing its dynamism and predictive accuracy.
评估健康城市是实现 "将健康纳入所有政策 "这一概念的重要战略。然而,目前大多数健康城市的定量评估方法都以城市层面为主,往往忽略了城市内部的评估。基于地理空间案例推理(CBR)的概念,我们提出了一种创新的健康城市空间案例推理(HCSCBR)模型。该模型全面整合了影响城市健康的空间关系和属性特征。我们使用英国伯明翰中层超级产出区(MSOA)健康环境决定因素的详细多源数据集进行了实验。结果表明,我们的方法在分类性能上超越了传统的数据挖掘技术,比传统的 CBR 模型具有更高的准确性和效率。这种方法的灵活性使其不仅能应用于城市内的健康评估,还能扩展到城市间的评估。我们的研究结论是,HCSCBR 模型通过纳入空间关系,显著提高了健康城市评估的精确度和可靠性。此外,该模型的适应性和效率使其成为城市规划者和公共卫生研究人员的重要工具。未来的研究将侧重于整合时间维度,进一步增强和完善健康城市评估模型,从而提高其动态性和预测准确性。
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引用次数: 0
Analysis of Road Safety Perception and Influencing Factors in a Complex Urban Environment—Taking Chaoyang District, Beijing, as an Example 复杂城市环境中的道路安全认知及影响因素分析--以北京市朝阳区为例
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-31 DOI: 10.3390/ijgi13080272
Xinyu Hou, Peng Chen
Measuring human perception of environmental safety and quantifying the street view elements that affect human perception of environmental safety are of great significance for improving the urban environment and residents’ safety perception. However, domestic large-scale quantitative research on the safety perception of Chinese local cities needs to be deepened. Therefore, this paper chooses Chaoyang District in Beijing as the research area. Firstly, the network safety perception distribution of Chaoyang District is calculated and presented through the CNN model trained based on the perception dataset constructed by Chinese local cities. Then, the street view elements are extracted from the street view images using image semantic segmentation and target detection technology. Finally, the street view elements that affect the road safety perception are identified and analyzed based on LightGBM and SHAP interpretation framework. The results show the following: (1) the overall safety perception level of Chaoyang District in Beijing is high; (2) the number of motor vehicles and the proportion of the area of roads, skies, and sidewalks are the four factors that have the greatest impact on environmental safety perception; (3) there is an interaction between different street view elements on safety perception, and the proportion and number of street view elements have interaction on safety perception; (4) in the sections with the lowest, moderate, and highest levels of safety perception, the influence of street view elements on safety perception is inconsistent. Finally, this paper summarizes the results and points out the shortcomings of the research.
测量人类对环境安全的感知,量化影响人类环境安全感知的街景要素,对于改善城市环境和居民安全感知具有重要意义。然而,国内对地方城市安全感知的大规模定量研究还有待深化。因此,本文选择北京市朝阳区作为研究区域。首先,通过基于中国地级市构建的感知数据集训练的 CNN 模型,计算并呈现朝阳区的网络安全感知分布。然后,利用图像语义分割和目标检测技术从街景图像中提取街景要素。最后,基于 LightGBM 和 SHAP 解释框架对影响道路安全感知的街景元素进行识别和分析。结果显示如下(1)北京市朝阳区整体安全感知水平较高;(2)机动车数量和道路、天空、人行道面积比例是对环境安全感知影响最大的四个因素;(3)不同街景要素对安全感知存在交互作用,街景要素比例和数量对安全感知存在交互作用;(4)在安全感知水平最低、中等和最高的路段,街景要素对安全感知的影响不一致。最后,本文对研究结果进行了总结,并指出了研究的不足之处。
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引用次数: 0
Multi-Criteria Decision Analysis to Evaluate the Geographic Potential of Alternative Photovoltaic Types 评估替代光伏类型地理潜力的多标准决策分析
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-30 DOI: 10.3390/ijgi13080269
Franziska Hübl, Franz Welscher, Johannes Scholz
This paper contributes to the expansion of green energy production, which is being pursued in order to mitigate climate change and carbon emissions from energy production. It addresses the delineation of areas that are suitable for the application of photovoltaics in the context of agricultural areas, water bodies, and parking spaces. Three specific photovoltaic types are examined in order to find out which criteria influence their geographic potential and whether spatial multi-criteria decision analysis methods are suitable for identifying suitable areas. The proposed approach consists of four steps: (1) collecting factors through expert interviews and questionnaires; (2) mapping the criteria to the spatial datasets; (3) deriving weighted scores for individual criteria through expert interviews; (4) applying the multi-criteria decision analysis method to compute and aggregate the final scores. We test our methodology at selected sites in the state of Styria, Austria. The test sites represent the topographical characteristics of the state and are about 5% of the size of Styria, approximately 820 km2. The key contributions are a weighted set of criteria that are relevant for the geographic potential of alternative photovoltaic types and the developed methodology to determine this potential.
本文有助于扩大绿色能源生产,以减缓气候变化和能源生产中的碳排放。本文探讨了适合在农业区、水体和停车场应用光伏技术的区域划分问题。研究了三种特定的光伏类型,以找出影响其地理潜力的标准,以及空间多标准决策分析方法是否适用于确定合适的区域。建议的方法包括四个步骤:(1) 通过专家访谈和问卷调查收集因素;(2) 将标准映射到空间数据集;(3) 通过专家访谈得出单个标准的加权分数;(4) 应用多标准决策分析方法计算和汇总最终分数。我们在奥地利施蒂里亚州的选定地点测试了我们的方法。测试地点代表了该州的地形特征,约占施蒂里亚州面积的 5%,约 820 平方公里。我们的主要贡献在于制定了一套与替代光伏类型的地理潜力相关的加权标准,并开发了确定这种潜力的方法。
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引用次数: 0
Challenges to Viticulture in Montenegro under Climate Change 气候变化对黑山葡萄栽培的挑战
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-30 DOI: 10.3390/ijgi13080270
António Fernandes, Nataša Kovač, Hélder Fraga, André Fonseca, Sanja Šućur Radonjić, Marko Simeunović, Kruna Ratković, Christoph Menz, Sergi Costafreda-Aumedes, João A. Santos
The Montenegrin climate is characterised as very heterogeneous due to its complex topography. The viticultural heritage, dating back to before the Roman empire, is settled in a Mediterranean climate region, located south of the capital Podgorica, where climate conditions favour red wine production. However, an overall increase in warmer and drier periods affects traditional viticulture. The present study aims to discuss climate change impacts on Montenegrin viticulture. Bioclimatic indices, ensembled from five climate models, were analysed for both historical (1981–2010) and future (2041–2070) periods upon three socio-economic pathways: SSP1-2.6, SSP3-7.0 and SSP5-8.5. CHELSA (≈1 km) was the selected dataset for this analysis. Obtained results for all scenarios have shown the suppression of baseline conditions for viticulture. The average summer temperature might reach around 29.5 °C, and the growing season average temperature could become higher than 23.5 °C, advancing phenological events. The Winkler index is estimated to range from 2900 °C up to 3100 °C, which is too hot for viticulture. Montenegrin viticulture requires the application of adaptation measures focused on reducing temperature-increase impacts. The implementation of adaptation measures shall start in the coming years, to assure the lasting productivity and sustainability of viticulture.
由于地形复杂,黑山的气候特征非常多变。位于首都波德戈里察南部的地中海气候区的葡萄栽培传统可追溯到罗马帝国之前,那里的气候条件有利于红葡萄酒的生产。然而,气候变暖和干旱期的总体增加影响了传统的葡萄栽培。本研究旨在讨论气候变化对黑山葡萄栽培的影响。本研究根据三种社会经济路径,分析了由五个气候模型组合而成的历史(1981-2010 年)和未来(2041-2070 年)时期的生物气候指数:SSP1-2.6、SSP3-7.0 和 SSP5-8.5。本次分析选择了 CHELSA(≈1 km)数据集。所有方案的结果都表明,葡萄栽培的基准条件受到抑制。夏季平均气温可能达到 29.5 °C左右,生长季节平均气温可能高于 23.5 °C,使物候期提前。温克勒指数估计在 2900 °C 至 3100 °C 之间,这对葡萄栽培来说太热了。黑山葡萄栽培需要采取适应措施,重点是减少温度升高的影响。适应措施应在未来几年开始实施,以确保葡萄栽培的持久生产力和可持续性。
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引用次数: 0
The Spatial Equilibrium Model of Elderly Care Facilities with High Spatiotemporal Sensitivity and Its Economic Associations Study 高时空敏感性养老机构空间均衡模型及其经济关联研究
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-27 DOI: 10.3390/ijgi13080268
Hongyan Li, Rui Li, Jing Cai, Shunli Wang
The global population aging poses new challenges in allocating care facilities for the elderly. This demographic trend also influences economic development and the quality of urban life. However, current research focuses on the supply of elderly care facilities and primarily uses administrative divisions as a scale, resulting in low spatiotemporal sensitivity in evaluating the spatial equilibrium of elderly care facilities (SEECF). The relationship between the SEECF and economic development is not clear. In response to these problems, we proposed a spatial equilibrium model of elderly care facilities with high spatiotemporal sensitivity (SEM-HSTS) and explored the spatiotemporal associations between the SEECF and economic development. Considering the spatial accessibility rate of elderly care services (SARecs) and the spatiotemporal supply–demand ratio for elderly care services (STSDRecs), two types of supply–demand relationship factors were constructed. Then, a spatiotemporal accessibility of medical services (STAms) factor was obtained based on a modified two-step floating catchment area (M2SFCA) method. On this basis, the SEM-HSTS was constructed based on the theory of coordinated development. Further, a panel threshold model was employed to evaluate the influence relationships among population aging, SEECF, and gross domestic product (GDP) in different phases. Finally, spatial autocorrelation and Geodetector explored the spatial associations between SEECF and GDP across complex urban land use categories (ULUC). The experimental results at a 100-m grid scale showed that the SEM-HSTS exhibited higher spatiotemporal heterogeneity than the classical accessibility method, with elevated spatiotemporal sensitivity. Effectively identified various spatial imbalances, such as undersupply and resource waste. The panel model captured phased relationship changes, showing that SEECF had inhibitory and promotional effects on GDP in pre- and post-aging societies, with stronger effects as balance approached. Moreover, the combined interaction of ULUC and GDP had a more significant influence on SEECF than any individual factor, with GDP exerting a more significant influence. This study provides an empirical basis for creating resource-efficient elderly care facility systems and optimizing layouts.
全球人口老龄化给老年人护理设施的分配带来了新的挑战。这一人口趋势也影响着经济发展和城市生活质量。然而,目前的研究侧重于养老设施的供给,主要以行政区划为尺度,导致评估养老设施空间均衡(SEECF)的时空敏感性较低。同时,SEECF 与经济发展之间的关系也不明确。针对这些问题,我们提出了高时空敏感性的养老设施空间均衡模型(SEM-HSTS),并探讨了 SEECF 与经济发展之间的时空关联。考虑到养老服务空间可达率(SARecs)和养老服务时空供求比(STSDRecs),构建了两类供求关系因子。然后,根据修正的两步浮动集水区(M2SFCA)方法,得到了医疗服务时空可达性(STAms)因子。在此基础上,根据协调发展理论构建了 SEM-HSTS。然后,运用面板阈值模型评估了不同阶段人口老龄化、SEECF 和国内生产总值(GDP)之间的影响关系。最后,空间自相关和 Geodetector 探索了 SEECF 和 GDP 在复杂的城市土地利用类别(ULUC)中的空间关联。100 米网格尺度的实验结果表明,与经典的可达性方法相比,SEM-HSTS 表现出更高的时空异质性,具有更高的时空敏感性。有效识别了各种空间失衡现象,如供应不足和资源浪费。面板模型捕捉到了阶段性的关系变化,表明 SEECF 在老龄化前和老龄化后社会中对 GDP 有抑制和促进作用,随着平衡的临近,抑制和促进作用更强。此外,ULUC 和 GDP 的综合交互作用对 SEECF 的影响比任何单独因素都要显著,其中 GDP 的影响更为显著。这项研究为创建资源节约型养老设施系统和优化布局提供了实证依据。
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引用次数: 0
Built Environment Effect on Metro Ridership in Metropolitan Area of Valparaíso, Chile, under Different Influence Area Approaches 不同影响区方法下建筑环境对智利瓦尔帕莱索大都市区地铁乘客量的影响
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-26 DOI: 10.3390/ijgi13080266
Vicente Aprigliano, Sebastian Seriani, Catalina Toro, Gonzalo Rojas, Mitsuyoshi Fukushi, Marcus Cardoso, Marcelino Aurelio Vieira da Silva, Cristo Cucumides, Ualison Rébula de Oliveira, Cristián Henríquez, Andreas Braun, Volker Hochschild
The growing relevance of promoting a transition of urban mobility toward more sustainable modes of transport is leading to efforts to understand the effects of the built environment on the use of railway systems. In this direction, there are challenges regarding the creation of coherence between the locations of metro stations and their surroundings, which has been explored extensively in the academic community. This process is called Transit-Oriented Development (TOD). Within the context of Latin America, this study seeks to assess the influence of the built environment on the metro ridership in the metropolitan area of Valparaíso, Chile, testing two approaches of influence area definition, one of which is a fixed distance from the stations, and the other is based on the origin and destination survey of the study area. The analysis is based on Ordinary Least Squares regression (OLS) to identify the factors from the built environment, which affects the metro’s ridership. Results show that the models based on the area of influence defined through the use of the origin and destination survey explain the metro ridership better. Moreover, this study reveals that the metro system in Greater Valparaíso was not planned in harmony with urban development. The models demonstrate an inverse effect of the built environment on ridership, contrasting with the expected outcomes of a metro station designed following a Transit-Oriented Development approach.
促进城市交通向更可持续的交通方式过渡的重要性日益凸显,这促使人们努力了解建筑环境对铁路系统使用的影响。在这方面,地铁站位置与周边环境之间的协调性面临挑战,学术界对此进行了广泛探讨。这一过程被称为 "以交通为导向的发展"(TOD)。在拉丁美洲的背景下,本研究试图评估建筑环境对智利瓦尔帕莱索大都市区地铁乘客数量的影响,测试了两种影响区域的定义方法,一种是与车站的固定距离,另一种是基于研究区域的出发地和目的地调查。分析以普通最小二乘法回归(OLS)为基础,以确定影响地铁乘客人数的建筑环境因素。结果表明,通过使用出发地和目的地调查来界定影响区域的模型能够更好地解释地铁乘客数量。此外,这项研究还表明,大瓦尔帕莱索地区的地铁系统规划与城市发展并不协调。这些模型表明,建筑环境对乘客数量的影响是反向的,这与按照公交导向发展方法设计地铁站的预期结果形成了鲜明对比。
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引用次数: 0
Automatic Vehicle Trajectory Behavior Classification Based on Unmanned Aerial Vehicle-Derived Trajectories Using Machine Learning Techniques 利用机器学习技术,基于无人机得出的轨迹对车辆轨迹行为进行自动分类
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-26 DOI: 10.3390/ijgi13080264
Tee-Ann Teo, Min-Jhen Chang, Tsung-Han Wen
This study introduces an innovative scheme for classifying uncrewed aerial vehicle (UAV)-derived vehicle trajectory behaviors by employing machine learning (ML) techniques to transform original trajectories into various sequences: space–time, speed–time, and azimuth–time. These transformed sequences were subjected to normalization for uniform data analysis, facilitating the classification of trajectories into six distinct categories through the application of three ML classifiers: random forest, time series forest (TSF), and canonical time series characteristics. Testing was performed across three different intersections to reveal an accuracy exceeding 90%, underlining the superior performance of integrating azimuth–time and speed–time sequences over conventional space–time sequences for analyzing trajectory behaviors. This research highlights the TSF classifier’s robustness when incorporating speed data, demonstrating its efficiency in feature extraction and reliability in intricate trajectory pattern handling. This study’s results indicate that integrating direction and speed information significantly enhances predictive accuracy and model robustness. This comprehensive approach, which leverages UAV-derived trajectories and advanced ML techniques, represents a significant step forward in understanding vehicle trajectory behaviors, aligning with the goals of enhancing traffic control and management strategies for better urban mobility.
本研究采用机器学习(ML)技术,将原始轨迹转换为各种序列:时空、速度-时间和方位-时间,从而提出了一种创新方案,用于对无人驾驶航空飞行器(UAV)产生的飞行轨迹行为进行分类。对这些转换后的序列进行归一化处理,以便进行统一的数据分析,通过应用三种 ML 分类器(随机森林、时间序列森林 (TSF) 和典型时间序列特征)将轨迹分为六个不同的类别。在三个不同的交叉路口进行了测试,结果显示准确率超过 90%,这突出表明在分析轨迹行为时,方位角-时间序列和速度-时间序列的整合性能优于传统的时空序列。这项研究凸显了 TSF 分类器在整合速度数据时的鲁棒性,证明了其在特征提取方面的效率以及在处理复杂轨迹模式方面的可靠性。研究结果表明,整合方向和速度信息可显著提高预测准确性和模型稳健性。这种综合方法利用了无人机衍生轨迹和先进的 ML 技术,在理解车辆轨迹行为方面迈出了重要一步,符合加强交通控制和管理策略以改善城市交通的目标。
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引用次数: 0
Exploring the Spatiotemporal Patterns of Passenger Flows in Expanding Urban Metros: A Case Study of Shenzhen 探索不断扩张的城市大都市的客流时空模式:深圳案例研究
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-26 DOI: 10.3390/ijgi13080267
Sirui Lv, Hu Yang, Xin Lu, Fan Zhang, Pu Wang
Despite extensive investigations on urban metro passenger flows, their evolving spatiotemporal patterns with the extensions of urban metro networks have not been well understood. Using Shenzhen as a case study city, our study initiates an investigation into this matter by analyzing the evolving network topology of Shenzhen Metro. Subsequently, leveraging long-term smart card data, we analyze the evolving spatiotemporal patterns of passenger flows and develop an analytical approach to pinpoint the major passenger sources of urban metro congestion. While the passenger travel demand and the passenger flow volumes kept increasing with the extension of the urban metro network, the major passenger sources were very stable in space, highlighting the inherent invariance in the evolution of the urban metro system. Finally, we analyze the impact of population and land use factors on passenger flow contributions of passenger sources, obtaining useful clues to foresee future passenger flow conditions.
尽管对城市地铁客流进行了广泛的研究,但人们对其随着城市地铁网络的延伸而不断演变的时空模式还不甚了解。本研究以深圳为案例城市,通过分析深圳地铁不断演变的网络拓扑结构,开始了对这一问题的研究。随后,我们利用长期的智能卡数据分析了客流的时空演变模式,并开发了一种分析方法来确定城市地铁拥堵的主要客源。虽然随着城市地铁网络的延伸,乘客出行需求和客流量不断增加,但主要客流来源在空间上却非常稳定,这凸显了城市地铁系统演变的内在不变性。最后,我们分析了人口和土地利用因素对客源客流贡献的影响,为预测未来客流状况提供了有用的线索。
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引用次数: 0
Building Height Extraction Based on Spatial Clustering and a Random Forest Model 基于空间聚类和随机森林模型的建筑高度提取技术
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-26 DOI: 10.3390/ijgi13080265
Jingxin Chang, Yonghua Jiang, Meilin Tan, Yunming Wang, Shaodong Wei
Building height (BH) estimation is crucial for urban spatial planning and development. BH estimation using digital surface model data involves obtaining ground and roof elevations. However, vegetation and shadows around buildings affect the selection of the required elevation, resulting in large BH estimation errors. In highly urbanized areas, buildings of similar heights often have similar characteristics and spatial proximity, which have reference significance in BH estimation but are rarely utilized. Herein, we propose a BH estimation method based on BIRCH clustering and a random forest (RF) model. We obtain the initial BH results using a method based on the optimal ground search area and a multi-index evaluation. BIRCH clustering and an RF classification model are used to match buildings of similar heights based on their spatial distance and attribute characteristics. Finally, the BH is adjusted based on the ground elevation obtained from the secondary screening and the BH matching. The validation results from two areas with over 12,000 buildings show that the proposed method reduces the root-mean-square error of the final BH results compared with the initial results. Comparing the obtained height maps shows that the final results produce a relatively accurate BH in areas with high shading and vegetation coverage, as well as in areas with dense buildings. Thus, the proposed method has been validated for its effectiveness and reliability.
建筑高度(BH)估算对于城市空间规划和发展至关重要。使用数字地表模型数据进行建筑物高度估算需要获取地面和屋顶标高。然而,建筑物周围的植被和阴影会影响所需标高的选择,从而导致较大的建筑物高度估算误差。在高度城市化的地区,高度相近的建筑物往往具有相似的特征和空间接近性,这在 BH 估算中具有参考意义,但却很少被利用。在此,我们提出了一种基于 BIRCH 聚类和随机森林 (RF) 模型的 BH 估算方法。我们使用基于最佳地面搜索区域和多指标评估的方法获得了初步的 BH 结果。BIRCH 聚类和 RF 分类模型用于根据空间距离和属性特征匹配高度相似的建筑物。最后,根据二次筛选和 BH 匹配得到的地面标高调整 BH。两个地区超过 12,000 栋建筑物的验证结果表明,与初始结果相比,建议的方法降低了最终 BH 结果的均方根误差。比较所获得的高度图可以看出,在阴影和植被覆盖率较高的地区以及建筑物密集的地区,最终结果都能产生相对准确的 BH。因此,建议的方法的有效性和可靠性得到了验证。
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引用次数: 0
Measuring Reliable Accessibility to High-Speed Railway Stations by Integrating the Utility-Based Model and Multimodal Space–Time Prism under Travel Time Uncertainty 在旅行时间不确定的情况下,通过整合基于效用的模型和多模式时空棱镜,测量高速铁路车站的可靠可达性
IF 3.4 3区 地球科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-07-25 DOI: 10.3390/ijgi13080263
Yongsheng Zhang, Kangyu Liang, Enjian Yao, Mingyi Gu
Measuring the accessibility of each traffic zone to high-speed railway stations can evaluate the ease of the transportation hub in the transportation system. The utility-based model, which captures individual travel behavior and subjective perception, is often used to quantify the travel impedance on accessibility for a given origin–destination pair. However, existing studies neglect the impacts of travel time uncertainty on utility and possible choice set when measuring accessibility, especially in high-timeliness travel (e.g., railway stations or airports). This study proposes a novel integration of the utility-based model and multimodal space–time prism under travel time uncertainty to measure reliable accessibility to high-speed railway stations. First, the reliable multimodal space–time prism is developed to generate a reliable travel mode choice set constrained by travel time budgets. Then, the reliable choice set is integrated into the utility-based model with the utility function derived from a proposed mean–standard deviation logit-based mode choice model. Finally, this study contributes to measuring reliable accessibility within areas from Beijing’s 5th Ring Road to the Beijing South Railway Station. Based on the results, policymakers can effectively evaluate the distribution of transportation resources and urban planning.
测量各交通区通往高速铁路车站的可达性可以评估交通枢纽在交通系统中的便利程度。基于效用的模型捕捉了个人的出行行为和主观感受,通常用于量化特定出发地-目的地对的出行障碍对可达性的影响。然而,现有研究在测量可达性时,忽略了旅行时间不确定性对效用和可能选择集的影响,尤其是在高时效性旅行中(如火车站或机场)。本研究提出了一种基于效用的模型和旅行时间不确定性下多模式时空棱镜的新整合方法,用于测量高速铁路车站的可靠可达性。首先,开发可靠的多模式时空棱镜,生成受旅行时间预算限制的可靠旅行模式选择集。然后,将可靠的选择集整合到基于效用的模型中,其效用函数来源于所提出的基于均值-标准差 logit 的模式选择模型。最后,本研究为测量从北京五环路到北京南站区域内的可靠可达性做出了贡献。根据研究结果,决策者可以有效评估交通资源的分配和城市规划。
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引用次数: 0
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ISPRS International Journal of Geo-Information
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