In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the tempor...In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.展开更多
Spatial vector data with high-precision and wide-coverage has exploded globally,such as land cover,social media,and other data-sets,which provides a good opportunity to enhance the national macroscopic decision-making...Spatial vector data with high-precision and wide-coverage has exploded globally,such as land cover,social media,and other data-sets,which provides a good opportunity to enhance the national macroscopic decision-making,social supervision,public services,and emergency capabilities.Simultaneously,it also brings great challenges in management technology for big spatial vector data(BSVD).In recent years,a large number of new concepts,parallel algorithms,processing tools,platforms,and applications have been proposed and developed to improve the value of BSVD from both academia and industry.To better understand BSVD and take advantage of its value effectively,this paper presents a review that surveys recent studies and research work in the data management field for BSVD.In this paper,we discuss and itemize this topic from three aspects according to different information technical levels of big spatial vector data management.It aims to help interested readers to learn about the latest research advances and choose the most suitable big data technologies and approaches depending on their system architectures.To support them more fully,firstly,we identify new concepts and ideas from numerous scholars about geographic information system to focus on BSVD scope in the big data era.Then,we conclude systematically not only the most recent published literatures but also a global view of main spatial technologies of BSVD,including data storage and organization,spatial index,processing methods,and spatial analysis.Finally,based on the above commentary and related work,several opportunities and challenges are listed as the future research interests and directions for reference.展开更多
【目的】掌握体力活动与建成环境特征的关联对主动干预公众健康具有重大意义。【方法】为系统地验证建成环境的移动型体力活动使用效能,根据自发地理信息、体力活动、环境特征等关键词从Web of Science等数据库筛选出31篇描述统计汇报...【目的】掌握体力活动与建成环境特征的关联对主动干预公众健康具有重大意义。【方法】为系统地验证建成环境的移动型体力活动使用效能,根据自发地理信息、体力活动、环境特征等关键词从Web of Science等数据库筛选出31篇描述统计汇报完整的学术论文,对文章信息、样本基本信息、研究分析方法、因变量和自变量信息等内容进行系统梳理,在此基础上对论文结果进行量化荟萃分析。【结果】自然环境、建成环境、社会环境及主观感知环境均与移动型体力活动存在一致的显著相关关系,关联程度因体力活动类型而异。自然环境中,归一化植被指数、绿化空间密度等自上而下的绿化水平与各类体力活动的正相关性最强;建成环境中,道路密度也与移动型体力活动存在一致的显著正相关关系,而便利设施的供给、人行道宽度仅对步行活动有积极的促进作用;除骑行活动外,居住用地密度与步行、跑步及一般体力活动都有显著的正相关关系。【结论】大批量、多尺度、高精度的体力活动自发地理信息有助于研究者客观掌握城市街区体力活动的分布,比较不同建成环境在多种时空尺度下的体力活动访问模式及使用效能,进而构建街区环境特征与体力活动适宜性的关联性模型;基于荟萃分析的发现为城市规划者和政策制定者优化和新建体力活动干预设施提供了使用效能预测的经验模型,有助于更科学合理地建设促进健康行为的人居环境。展开更多
基金Project(2014BAG01B0403)supported by the National High-Tech Research and Development Program of China
文摘In order to describe the characteristics of dynamic traffic flow and improve the robustness of its multiple applications, a dynamic traffic temporal-spatial model(DTTS) is established. With consideration of the temporal correlation, spatial correlation and historical correlation, a basic DTTS model is built. And a three-stage approach is put forward for the simplification and calibration of the basic DTTS model. Through critical sections pre-selection and critical time pre-selection, the first stage reduces the variable number of the basic DTTS model. In the second stage, variable coefficient calibration is implemented based on basic model simplification and stepwise regression analysis. Aimed at dynamic noise estimation, the characteristics of noise are summarized and an extreme learning machine is presented in the third stage. A case study based on a real-world road network in Beijing, China, is carried out to test the efficiency and applicability of proposed DTTS model and the three-stage approach.
基金This work is supported by the Strategic Priority Research Program of Chinese Academy of Sciences[grant number XDA19020201].
文摘Spatial vector data with high-precision and wide-coverage has exploded globally,such as land cover,social media,and other data-sets,which provides a good opportunity to enhance the national macroscopic decision-making,social supervision,public services,and emergency capabilities.Simultaneously,it also brings great challenges in management technology for big spatial vector data(BSVD).In recent years,a large number of new concepts,parallel algorithms,processing tools,platforms,and applications have been proposed and developed to improve the value of BSVD from both academia and industry.To better understand BSVD and take advantage of its value effectively,this paper presents a review that surveys recent studies and research work in the data management field for BSVD.In this paper,we discuss and itemize this topic from three aspects according to different information technical levels of big spatial vector data management.It aims to help interested readers to learn about the latest research advances and choose the most suitable big data technologies and approaches depending on their system architectures.To support them more fully,firstly,we identify new concepts and ideas from numerous scholars about geographic information system to focus on BSVD scope in the big data era.Then,we conclude systematically not only the most recent published literatures but also a global view of main spatial technologies of BSVD,including data storage and organization,spatial index,processing methods,and spatial analysis.Finally,based on the above commentary and related work,several opportunities and challenges are listed as the future research interests and directions for reference.
文摘【目的】掌握体力活动与建成环境特征的关联对主动干预公众健康具有重大意义。【方法】为系统地验证建成环境的移动型体力活动使用效能,根据自发地理信息、体力活动、环境特征等关键词从Web of Science等数据库筛选出31篇描述统计汇报完整的学术论文,对文章信息、样本基本信息、研究分析方法、因变量和自变量信息等内容进行系统梳理,在此基础上对论文结果进行量化荟萃分析。【结果】自然环境、建成环境、社会环境及主观感知环境均与移动型体力活动存在一致的显著相关关系,关联程度因体力活动类型而异。自然环境中,归一化植被指数、绿化空间密度等自上而下的绿化水平与各类体力活动的正相关性最强;建成环境中,道路密度也与移动型体力活动存在一致的显著正相关关系,而便利设施的供给、人行道宽度仅对步行活动有积极的促进作用;除骑行活动外,居住用地密度与步行、跑步及一般体力活动都有显著的正相关关系。【结论】大批量、多尺度、高精度的体力活动自发地理信息有助于研究者客观掌握城市街区体力活动的分布,比较不同建成环境在多种时空尺度下的体力活动访问模式及使用效能,进而构建街区环境特征与体力活动适宜性的关联性模型;基于荟萃分析的发现为城市规划者和政策制定者优化和新建体力活动干预设施提供了使用效能预测的经验模型,有助于更科学合理地建设促进健康行为的人居环境。
