The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and i...The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.展开更多
The surging accumulation of trajectory data has yielded invaluable insights into urban systems,but it has also presented challenges for data storage and management systems.In response,specialized storage systems based...The surging accumulation of trajectory data has yielded invaluable insights into urban systems,but it has also presented challenges for data storage and management systems.In response,specialized storage systems based on non-relational databases have been developed to support large data quantities in distributed approaches.However,these systems often utilize storage by point or storage by trajectory methods,both of which have drawbacks.In this study,we evaluate the effectiveness of segmented trajectory data storage with HBase optimizations for spatio-temporal queries.We develop a prototype system that includes trajectory segmentation,serialization,and spatio-temporal indexing and apply it to taxi trajectory data in Beijing.Ourfindings indicate that the segmented system provides enhanced query speed and reduced memory usage compared to the Geomesa system.展开更多
基金supported by the National Natural Science Foundation of China (71991484,42271471,72088101,and 41830645)Danish Agency for Higher Education and Science (International Network Project,0192-00056B)the Fundamental Research Funds for the Central Universities (Peking University).
文摘The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important,yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources,waste,and climate strategies.However,our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited,largely owing to the lack of sufficient high spatial resolution data.This study leveraged multi-source big geodata,machine learning,and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels.The per capita built environment stock of many cities(261 tonnes per capita on average)is close to that in western cities,despite considerable disparities across cities owing to their varying socioeconomic,geomorphology,and urban form characteristics.This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades.China’s urban expansion tends to be more“vertical”(with high-rise buildings)than“horizontal”(with expanded road networks).It trades skylines for space,and reflects a concentration-dispersion-concentration pathway for spatialized built environment stocks development within cities in China.These results shed light on future urbanization in developing cities,inform spatial planning,and support circular and low-carbon transitions in cities.
基金support from the National Natural Science Foundation of China(42271471,42201454,41830645)the International Research Center of Big Data for Sustainable Development Goals(CBAS2022GSP06).
文摘The surging accumulation of trajectory data has yielded invaluable insights into urban systems,but it has also presented challenges for data storage and management systems.In response,specialized storage systems based on non-relational databases have been developed to support large data quantities in distributed approaches.However,these systems often utilize storage by point or storage by trajectory methods,both of which have drawbacks.In this study,we evaluate the effectiveness of segmented trajectory data storage with HBase optimizations for spatio-temporal queries.We develop a prototype system that includes trajectory segmentation,serialization,and spatio-temporal indexing and apply it to taxi trajectory data in Beijing.Ourfindings indicate that the segmented system provides enhanced query speed and reduced memory usage compared to the Geomesa system.
