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1.
Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model 总被引：1，自引：0，他引：1
Yao Yao Penghua Liu Zhaotang Liang Jinbao Zhang 《International journal of geographical information science》2017,31(4):825-848
Urban land use information plays an essential role in a wide variety of urban planning and environmental monitoring processes. During the past few decades, with the rapid technological development of remote sensing (RS), geographic information systems (GIS) and geospatial big data, numerous methods have been developed to identify urban land use at a fine scale. Points-of-interest (POIs) have been widely used to extract information pertaining to urban land use types and functional zones. However, it is difficult to quantify the relationship between spatial distributions of POIs and regional land use types due to a lack of reliable models. Previous methods may ignore abundant spatial features that can be extracted from POIs. In this study, we establish an innovative framework that detects urban land use distributions at the scale of traffic analysis zones (TAZs) by integrating Baidu POIs and a Word2Vec model. This framework was implemented using a Google open-source model of a deep-learning language in 2013. First, data for the Pearl River Delta (PRD) are transformed into a TAZ-POI corpus using a greedy algorithm by considering the spatial distributions of TAZs and inner POIs. Then, high-dimensional characteristic vectors of POIs and TAZs are extracted using the Word2Vec model. Finally, to validate the reliability of the POI/TAZ vectors, we implement a K-Means-based clustering model to analyze correlations between the POI/TAZ vectors and deploy TAZ vectors to identify urban land use types using a random forest algorithm (RFA) model. Compared with some state-of-the-art probabilistic topic models (PTMs), the proposed method can efficiently obtain the highest accuracy (OA = 0.8728, kappa = 0.8399). Moreover, the results can be used to help urban planners to monitor dynamic urban land use and evaluate the impact of urban planning schemes. 相似文献
2.
移动定位大数据视角下的人群移动模式及城市空间结构研究进展 总被引：5，自引：3，他引：2
了解城市人群移动行为和空间结构对城市规划、交通管理、应急响应等具有重要的意义。近年来,随着信息技术(ICT)的快速发展,采集大规模、长时间序列的人群移动定位大数据变得容易,为人群移动行为研究带来了新的机遇和挑战。本文首先介绍了目前用于城市人群移动行为和空间结构研究的主要数据源及其特征,并分别从人群移动行为、城市空间结构2个方面对近3年国内外相关研究进行归纳总结。目前的研究主要从移动定位大数据中挖掘人群移动模式,理解人群移动时空规律,进一步透视城市的空间结构特征;而对城市空间结构与人群移动行为影响的研究较少。未来可通过融合多源时空数据,综合研究人群移动行为与城市空间结构之间的相互作用,发展大规模群体移动行为时空分析理论和模型,进一步深入理解人群移动行为与城市空间结构的耦合关系。 相似文献
3.
The focus of methodological approaches to identify (public) service deprivation has been predominantly on the shortcomings in the spatial coverage of the transportation system and the urban opportunity landscape. Accessibility is thereby generally modeled as a static concept with little - if any - account for temporal variations in services and transportation provision across the diurnal cycle and week, such as those resulting from opening hours and congestion effects. This paper suggests the use of time-specific measures of service accessibility and demand. The measures are integrated in a GIS-based multi-criteria analysis with the aim to detect spatiotemporal variations in service deprivation. The applicability of the method has been illustrated in a case study about the planning of a mobile government office bus in the city of Ghent (Belgium). It has been shown that the suitability of alternative stop locations for the bus depends on the time interval during which it will be operated. 相似文献
4.
广州市地铁可达性时空演化及其对公交可达性的影响 总被引：5，自引：1，他引：4
应用GIS方法,选取2000、2003、2009和2012年4个时间节点,运用复杂网络理论构建了广州市公共交通网络模型,通过对比分析地铁站点与线路加入到公共交通网络中所产生的变化,定量分析地铁网络建设对公共交通可达性的影响,分析地铁发展不同时期内,城市公共交通可达性空间格局的演化,全面探讨地铁建设对城市公共交通可达性的影响,以期为一体化的多模式城市公共交通体系发展决策提供理论支持。结果显示:①广州市地铁网络顺利完成由树状向回路网络的转变,地铁可达性重心与广州市空间扩展方向呼应,呈现出向南、向东迁移特征;②地铁在很大程度上提高了广州城市公交网络可达性,且其改善作用随地铁线路网的增加和回路网络的发育而日益显著;③地铁网络对城市公交可达性格局的影响,打破了常规公交网络圈层式公交可达性格局,逐渐呈现出圈层式加沿地铁线路分布的廊道式格局;④地铁对公交各站点网络可达时间的影响,常规公交站点可达时间变化程度呈现出由地铁线路向外递减的空间分布趋势,当地铁网络发育形成回路网络时,大大地提升公交网络的运营效率,缩短各个站点之间的出行时间。 相似文献
5.
基于居民行为周期特征的城市空间研究 总被引：4，自引：1，他引：3
伴随着中国经济社会进入“新常态”的发展阶段,对城市存量空间的研究提出了更加精细化的要求,基于居民行为活动的周期规律对城市空间进行研究,进而提升城市空间的品质日益重要。随着信息通信技术的快速发展,使许多大数据的获取成为可能,并由于其低成本、即时、大样本等优势,在城市空间研究方面具有巨大的价值。以上海市中心城区为例,利用手机信令数据,探究居民活动的空间周期变化特征,并基于空间的周期特征曲线,采用相似性传播聚类算法进行空间分类。研究表明,居民活动有平日一日周期和平日加周末二日周期,与人的作息规律相符合。市核心区、城市副中心及主要就业中心,昼夜波动和平日周末活动强度的差异都较为明显。空间分类结果显示,城市活动空间的组织既体现出个体充分的空间能动性,也反映出对土地使用类型以及设施建设、投入程度的耦合性。上海市内环内核心区混合多样的用地模式使得活动区内居民活动内容丰富,周期特征功能区边界模糊。研究成果可为未来的城市空间规划提供指导,为城市空间结构、功能布置、设施布局等优化提供决策支撑和科学依据。 相似文献
6.
北京城区公共交通满意度模型与空间结构评价 总被引：5，自引：1，他引：4
以北京市城八氏的公共交通为切入点.探索了城市空间结构的评价分析方法.通过"公共交通可达性"指标.将城市实体空间结构的指标与居民对公共交通的满意度连系起来.建立了以满意度为目标的城市空间结构评价体系.并对提升城市空间结构的实体空间因子进行了实证分析.首先,对"公共交通可达性"的各项影响因子进行了梳理,从公共交通服务质量、区域经济特征、道路建设三个方面,提出了包括公交通达度、人口和经济集聚度、道路密度、区位指标等在内的城市公共交通可达性的评价指标体系.其次,构建了以居民满意度为因变量的公共交通可达性评价模型.分析定量揭示了公交站点配置、公交通达度、经济密度等凶素对了:城市空间结构的优化作用.同时分析表明.公共交通的优化需充分考虑不同属性的居民群体的空间分布规律.据此,从城市空间结构评价的角度分析了北京市公共交通中存在的问题,并提出如下建议:①市政交通规划的重点应放在五环以内地区;②实现800m公交站点服务面积全覆盖;③加强各地与市区重要功能节点的公共交通联系来提高其通达度;④根据居民的分布和属性特征出台相应的公交服务政策提高不同居民群体的公共交通满意度. 相似文献
7.
中国时空间行为研究进展 总被引：11，自引：4，他引：7
自时间地理学和活动分析法引入中国以来的近20年间,时空间行为研究已经成为中国城市地理学的重要领域。中国时空间行为研究关注城市空间重构的描述与解释,试图从行为角度解释中国城市社会转型,强调转型期中国城市空间与居民个体行为之间的互动关系,重视日常生活、生活质量、社会公正、低碳社会、智慧城市等热点问题,探索在城市交通、旅游和城市规划等领域中的实践应用。中国时空间行为研究已经形成了以解读城市转型为目标、以规划应用为导向的鲜明特点,为理解中国城市制度与空间转型背景下人类行为模式的复杂性和多样性提供了一个全新的视角。但是,中国时空间行为研究依然面临着理论发展滞后、实践应用需要突破等挑战。本文是对时空行为研究近年来发展的综述性文章,从数据采集与分析方法演进、实证研究与规划应用进展等方面回顾了近20年来中国城市时空间行为研究的最新进展,致力于推动不同学科领域之间的交流和时空间行为研究自身的发展。 相似文献
8.
Analyzing the distribution of human activity space from mobile phone usage: an individual and urban-oriented study 总被引：1，自引：0，他引：1
Yihong Yuan Martin Raubal 《International journal of geographical information science》2016,30(8):1594-1621
Travel activities are embodied as people’s needs to be physically present at certain locations. The development of Information and Communication Technologies (ICTs, such as mobile phones) has introduced new data sources for modeling human activities. Based on the scattered spatiotemporal points provided in mobile phone datasets, it is feasible to study the patterns (e.g., the scale, shape, and regularity) of human activities. In this paper, we propose methods for analyzing the distribution of human activity space from both individual and urban perspectives based on mobile phone data. The Weibull distribution is utilized to model three predefined measurements of activity space (radius, shape index, and entropy). The correlation between demographic factors (age and gender) and the usage of urban space is also tested to reveal underlying patterns. The results of this research will enhance the understanding of human activities in different urban systems and demographic groups, as well as providing novel methods to expand the important and widely applicable area of geographic knowledge discovery in the age of instant access. 相似文献
9.
城市绿色空间格局时空演变及其生态系统服务评价的研究进展与展望 总被引：2，自引：1，他引：1
科学合理的城市绿色空间格局是城市可持续发展的物质空间保障,对其时空演变和影响因素进行研究,可揭示城市绿色空间在城市化进程中各要素与演变过程的复杂关系,以确保城市生态系统服务功能的正常发挥。在生态文明建设背景下,城市绿色空间将在多尺度国土空间规划中发挥积极作用,然而城市绿色空间规划与国土空间规划如何衔接却有待商榷。因此,论文在梳理城市绿色空间概念界定和发展历程的基础上,一方面讨论城市绿色空间格局的时空评价、驱动因子、情景模拟及优化策略的研究进展;另一方面总结生态系统服务在城市绿色空间格局评价中的应用进展。通过归纳以上研究内容,提出国土空间规划体系中有关城市绿色空间格局的评价及优化框架,以期为新时代背景下的城市绿色空间规划提供参考。 相似文献
10.
11.
Mingjia Chen Yingwei Yan Chen-Chieh Feng Shuting Chen Jing Wang Mengbi Ye 《Singapore journal of tropical geography》2023,44(3):414-437
The Mass Rapid Transit (MRT) is one of the major modes of public transportation in Singapore. Understanding the mobility patterns of MRT passengers has implications for improving transportation efficiency. As a city-state with a high population density, Singapore provides a representation of balanced urban dynamics that informs smart urban planning. In this paper, we investigated and visualized (using both static maps and dynamic web map applications) the spatiotemporal characteristics of Singapore's MRT commuting patterns before the COVID-19 pandemic (January 2020) and during the first outbreak (May 2020) and the Omicron wave of the pandemic (February 2022), using MRT smart card data. We also investigated the relationship between the passenger flows of individual MRT stations and the nearby land use types. Our results showed that the spatial patterns of Singapore's MRT commuters match the polycentric urban structure. In addition to central areas, several regional centres were identified as passenger hotspots in multiple time periods. Furthermore, during the outbreak of the pandemic, especially in the period of the ‘circuit breaker’, there was a major decline in MRT passenger flows and a decrease in average MRT commuting distances during weekend/holiday peak hours. Lastly, correlations between passenger flows of MRT stations and the proportion of nearby land use types have been identified. 相似文献
12.
Coupling mobile phone and social media data: a new approach to understanding urban functions and diurnal patterns 总被引：1，自引：0，他引：1
Wei Tu Jinzhou Cao Shih-Lung Shaw Meng Zhou Zhensheng Wang 《International journal of geographical information science》2017,31(12):2331-2358
Understanding urban functions and their relationships with human activities has great implications for smart and sustainable urban development. In this study, we present a novel approach to uncovering urban functions by aggregating human activities inferred from mobile phone positioning and social media data. First, the homes and workplaces (of travelers) are estimated from mobile phone positioning data to annotate the activities conducted at these locations. The remaining activities (such as shopping, schooling, transportation, recreation and entertainment) are labeled using a hidden Markov model with social knowledge learned from social media check-in data over a lengthy period. By aggregating identified human activities, hourly urban functions are inferred, and the diurnal dynamics of those functions are revealed. An empirical analysis was conducted for the case of Shenzhen, China. The results indicate that the proposed approach can capture citywide dynamics of both human activities and urban functions. It also suggests that although many urban areas have been officially labeled with a single land-use type, they may provide different functions over time depending on the types and range of human activities. The study demonstrates that combining different data on human activities could yield an improved understanding of urban functions, which would benefit short-term urban decision-making and long-term urban policy making. 相似文献
13.
Wei Huang 《International journal of geographical information science》2019,33(2):385-407
A mechanistic understanding of human activity patterns lays a foundation for many applications. The majority of the current research aims to outline human activity patterns mainly from spatiotemporal perspectives (i.e., modeling human mobility patterns), lacking of understanding of the motivations behind behaviors. The aim of this study is to model and understand human activity patterns within urban areas using both spatiotemporal and cognitive psychology methods to measure both human behavior patterns and the underlying motivations . We first propose a framework that enables us to analyze the spatiotemporal patterns of urban human activities, infer the associated semantic patterns that represent the motivations driving human mobility choices and behaviors, and measure the similarity between human activities. We then construct a human activity network based on the similarity to depict human activity patterns. The framework is applied to a case study of Toronto, Canada, where geotagged tweets are used as a proxy for human activities to explore activity patterns. The analysis of the human activity network shows that 61% of tweeter users follow similar activity patterns. Our work provides a new tool for better understanding the way individuals interact with urban environments that could be applied\ to a variety of urban applications. 相似文献
14.
城市交通热点区域的空间交互网络分析 总被引：1，自引：0，他引：1
城市热点区域是人们频繁活动的体现,利用人们的出行可构建空间交互网络。目前的相关研究主要集中于对热点提取方法及其动态变化的研究,对交通热点的交互作用及其构成的空间交互网络的研究还很少。本文以武汉市的出租车轨迹为数据源,利用基于时空数据场的聚类方法提取城市交通热点区域;基于复杂网络理论与方法,分析城市交通热点区域之间的空间交互作用。通过研究发现：①节假日,热点区域之间的往返交互较多;工作日,热点区域之间的交互较少;②节假日,影响力较大的节点为车站、机场等;工作日,影响力较大的节点是社区和工作地;③社团探测发现,工作日跨越长江的交互较多,非工作日跨越长江的交互较少。上述研究结论可为交通管理部门针对节假日和工作日分别制定不同的交通管理政策和方法提供参考。 相似文献
15.
社区生活圈的新时间地理学研究框架 总被引：5，自引：5，他引：0
社区生活圈从居民日常活动及行为视角考察城市社区,是城市地理学和城市相关学科的研究前沿,也是中国国土空间规划体系创新的重要组成部分,以及中国城市社会可持续发展的重要抓手。伴随着流动性和信息化的不断深入,社区生活圈的主体日益多元化、社区活动和居民时空行为日益多样化、社区空间的功能与意义日益丰富化,亟需城市地理学的研究创新与实践引导。时间地理学是理解人与环境关系的社会—技术—生态综合方法,为早期基于时空行为与生活空间的社区生活圈研究提供了重要基础。新时间地理学重视家庭及其他组织企划的交互与时空组合,可为社区生活圈内个体—家庭—社区之间的复杂互动关系研究、时空行为的社会文化制约与多情境分析及模拟提供重要支撑。论文基于新时间地理学方法,从理论、方法和实证3个维度提出社区生活圈的新时间地理学研究框架,具体包括构建社区生活圈的时空行为理论,揭示社区生活圈的时空间结构;创新社区生活圈的时空行为分析和模拟方法;从社区生活圈时空行为优化、社区交往生活圈、社区安全生活圈等方面创新中国城市规划与管理等研究内容。 相似文献
16.
大数据时代的空间交互分析方法和应用再论 总被引：10，自引：1，他引：9
空间交互是理解地表人文过程的重要基础,与空间依赖一起共同体现了地理空间的独特性、关联性以及对嵌入该空间的地理分布格局的影响,具有鲜明的时空属性,因此对于地理学研究具有重要意义。大数据为空间交互研究带来了新的机遇,能够使我们在不同时空尺度感知和观察空间交互模式并对其动态演化特征进行模拟和预测,从而为揭示人类活动规律及区域空间结构提供有力支持。本文在探讨空间交互与地理空间模式关系的基础上,描述了利用地理大数据感知空间交互的方式和定量模型,介绍了空间交互分析方法的研究进展及其在空间规划与交通、公共卫生、旅游等领域的应用情况,并就一些基本问题进行了讨论,以期为大数据支持下空间交互相关研究提供指导。 相似文献
17.
大数据时代,社交媒体的大量应用为研究游客情感体验以及探索其时空变化提供了新的数据源。采集3 a间西安市国内游客微博签到数据,运用热点格网图法、Getis-Ord Gi*方法和X-means聚类方法,从积极情感和消极情感2个维度研究西安市国内游客情感体验时空变化和演化规律。结果表明：（1） 城市中心、城市主轴线、主要商圈以及景区景点附近游客情感相对较高且稳定,高情感体验区域主要分布在曲江新区和西安古城旅游区。（2） 消极情感体验在西安的交通枢纽和城市边缘的空间占比高,交通枢纽主要以车站、城市进出口为主。（3） 整体上来看,3 a间西安市游客情感较为平稳,积极情感呈现“中心—边缘”的空间格局,消极情感和积极情感的呈现具有相似性,主要以3种类型为主：稳定型、相对稳定型和剧烈波动型。在3种类型中,稳定型的主要聚集地在城市中心、商圈附近、交通干线周边以及景区景点附近,相对稳定型占据西安市大面积区域,剧烈波动型处于距离城市中心较远的边缘。 相似文献
18.
Carbon emissions caused by human activities are closely related to the process of urbanization, and urban land utilization, function vitality and traffic systems are three important factors that may influence the emission levels. For clarifying the space structure of a low-carbon eco-city, and combining the concept of “Combining Assessment with Construction” to track and contrast the construction of the low-carbon eco-city, this research selects quantifiable low-carbon eco-city spatial characteristics as indicators, and evaluates and analyzes the potential carbon emissions. Taking the Jinan Western New District as an example, diversity of construction land, travel carbon emission potential, and density and accessibility of adjacent road networks in the overall urban planning were measured. After the completion of the new urban area, the evaluation mainly reflected certain factors, such as the mixed degree of urban functions, the density of urban functions, the walking distance to bus stops and the density and number of bus stops. Dividing the levels and adding equal weights after index normalization, the carbon emission potential is evaluated at the two levels of the overall and fragmented areas. The results show that: (1) The low-carbon emission potential areas in the planning scheme basically reached the planned goals. (2) There is inconsistency between districts and indicators in the planning scheme. The diversity of construction land and the accessibility of the adjacent road network are relatively small; however, there is a large difference between the travel carbon emission potential and the road network accessibility. (3) Carbon emission potential after completion did not reach the planned expectation, and the low-carbon emission potential plots were concentrated in the Changqing Old City Area and Central Area of Dangjia Town Area. (4) The carbon emission indicators varied greatly in different areas, and there were serious imbalances in the density of public transportation lines and the mixed degree of urban functions. 相似文献
19.
A novel residual graph convolution deep learning model for short-term network-based traffic forecasting 总被引：1，自引：0，他引：1
Yang Zhang Tao Cheng Yibin Ren Kun Xie 《International journal of geographical information science》2020,34(5):969-995
ABSTRACT Short-term traffic forecasting on large street networks is significant in transportation and urban management, such as real-time route guidance and congestion alleviation. Nevertheless, it is very challenging to obtain high prediction accuracy with reasonable computational cost due to the complex spatial dependency on the traffic network and the time-varying traffic patterns. To address these issues, this paper develops a residual graph convolution long short-term memory (RGC-LSTM) model for spatial-temporal data forecasting considering the network topology. This model integrates a new graph convolution operator for spatial modelling on networks and a residual LSTM structure for temporal modelling considering multiple periodicities. The proposed model has few parameters, low computational complexity, and a fast convergence rate. The framework is evaluated on both the 10-min traffic speed data from Shanghai, China and the 5-min Caltrans Performance Measurement System (PeMS) traffic flow data. Experiments show the advantages of the proposed approach over various state-of-the-art baselines, as well as consistent performance across different datasets. 相似文献
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把握人类活动的时空特征是地理学研究中探究人地关系、提升人类福祉的重要基础和核心内容,日益普及的Wi-Fi网络能够为此提供可靠的数据支持。为明确Wi-Fi数据融入地理学研究的切入点和发展方向,论文通过与GPS、手机信令、蓝牙等位置感应数据的比较,认为Wi-Fi数据具有更高的采样精度和更强的采样代表性,能够获取个体在室内外各类城市空间的连续活动轨迹,支撑精细尺度下的人类活动研究。通过系统梳理人群活动状态监测、个体间的社会关系识别、建筑物的功能识别和降低隐私泄露风险等方面的研究进展,认为Wi-Fi数据将会在基于实时动态人口数据的城市功能设施规划、融合多源数据的人地关系探究、以居民福祉为导向的宜居城市建设等方面具有应用前景,有望成为地理学研究人类活动的新支点。 相似文献