GeoSOT-Based Spatiotemporal Index of Massive Trajectory Data

Qian, Chunyao; Yi, Chao; Cheng, Chengqi; Pu, Guoliang; Wei, Xiaofeng; Zhang, Huangchuang

doi:10.3390/ijgi8060284

Cited by 34 publications

(25 citation statements)

References 28 publications

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“…The proposed air traffic highways in this research are constructed by 3D grids. Apart from UAV-related applications, GeoSOT-3D has been extensively investigated in remote sensing data management [ 38 , 39 ], city component identification [ 40 ], trajectory data storage [ 41 ], and urban expansion monitoring [ 42 ].…”

Section: Methodsmentioning

confidence: 99%

A low-altitude public air route network for UAV management constructed by global subdivision grids

et al. 2021

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With an increasing number of unmanned aerial vehicles (UAVs), the difficulty of UAV management becomes more challenging, especially for low-altitude airspace due to complicated issues of security, privacy and flexibility. Existing management approaches to UAV flights include implementing registration of flight activity for supervision purposes, limiting the maximum flight height, setting different zones for different flight activities and prohibiting flights. In this research, we proposed a new air traffic management method for UAVs based on global subdivision theory. We designed four types of low-altitude air routes from grids, which correspond to grid sizes of 1.85 km, 128 m, 64 m and 32 m. Utilization of the subdivision grids transforms the complex spatial computation problem into a query process in the spatial database, which provides a new approach to UAV management in the fifth-generation (5G) era. We compared the number and data size of stored track records using longitude and latitude and different grid levels, computed time consumption for air route trafficability and simulated UAV flight to verify the feasibility of constructing this type of air traffic highway system. The amount of data storage and time consumption for air route trafficability can be substantially reduced by subdivision. For example, the data size using traditional expressions of latitude and longitude is approximately 1.5 times that of using a 21-level grid, and the time consumption by coordinates is approximately 1.5 times that of subdivision grids at level 21. The results of the simulated experiments indicate that in the 5G environment, gridded airspace can effectively improve the efficiency of UAV trajectory planning and reduce the size of information storage in the airspace environment. Therefore, given the increasing number of UAVs in the future, gridded highways have the potential to provide a foundation for various UAV applications.

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Section: Methodsmentioning

confidence: 99%

A low-altitude public air route network for UAV management constructed by global subdivision grids

et al. 2021

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“…The spatiotemporal indexes constructed by the above methods can improve the spatiotemporal retrieval efficiency of remote-sensing data to a certain extent, but most of the algorithms use a simple spatiotemporal index superimposed on a secondary index to process the spatiotemporal data, and it needs to be filtered twice during a query, which reduces the indexing efficiency. Therefore, this study proposes a GeoSOT-ST-based data organization method, which converts high-dimensional time and space information into a onedimensional GeoSOT-ST [38], code, thereby effectively reducing the amount of conditional filtering in the query process. For remote-sensing metadata, an HBase database was chosen as the storage medium.…”

Section: B Spatiotemporal Organization and Indexing Of Metadatamentioning

confidence: 99%

An Efficient Organization Method for Large-Scale and Long Time-Series Remote Sensing Data in a Cloud Computing Environment

Yan

Liu

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Historical Earth observation (EO) data have played an important role in long-term scientific and environmental monitoring. The effective organization of large-scale and longterm remote-sensing data to achieve efficient retrieval and access has become one of the important issues. However, inherent big data characteristics, such as a large scale, and asymmetrical temporal and spatial distributions, have caused problems with the efficiency of data retrieval and access. Therefore, this study proposes an efficient data organization method for use in a cloudcomputing environment that has two aims. First, it addresses the problem of low retrieval efficiency. An asymmetrical index model for the image metadata is constructed that is based on a unified spatio-temporal grid coding; a pre-partitioning mechanism under the HBase architecture is established to realize the uniform storage of the metadata with an asymmetrical spatiotemporal distribution and to avoid retrieval efficiency bottlenecks caused by a load imbalance. Second, it addresses low access efficiency. By dividing the remote-sensing image into tiles, a unified spatiotemporal code is established for each tile, and a consistent hash operation is performed; tiles with similar hash values are stored in the same or adjacent HDFS (Hadoop Distributed File System) nodes. In this way, tiles with temporal or spatial correlations can be gathered and stored, and lots of disk seeks can be avoided during retrieval, thereby greatly improving the data access efficiency. Comparative experiments showed that the data organization method can effectively improve the retrieval and access efficiencies of large-scale and long time-series remotesensing data in a cloud-computing environment.

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“…These movement data are used to calculate intercity migration indices [27]. The use of travel-related big data with such high spatiotemporal resolution is more accurate and effective than the use of census data [28]. In this study, we used the population flow dataset from the AMAP Migration Map ("https://trp.autonavi.com/migrate/page.do").…”

Section: Study Datamentioning

confidence: 99%

Spatiotemporal Exploration of Chinese Spring Festival Population Flow Patterns and Their Determinants Based on Spatial Interaction Model

Zhou

Huang

Liu

et al. 2020

IJGI

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Large-scale population flow reshapes the economic landscape and is affected by unbalanced urban development. The exploration of migration patterns and their determinants is therefore crucial to reveal unbalanced urban development. However, low-resolution migration datasets and insufficient consideration of interactive differences have limited such exploration. Accordingly, based on 2019 Chinese Spring Festival travel-related big data from the AMAP platform, we used social network analysis (SNA) methods to accurately reveal population flow patterns. Then, with consideration of the spatial heterogeneity of interactive patterns, we used spatially weighted interactive models (SWIMs), which were improved by the incorporation of weightings into the global Poisson gravity model, to efficiently quantify the effect of socioeconomic factors on migration patterns. These SWIMs generated the local characteristics of the interactions and quantified results that were more regionally consistent than those generated by other spatial interaction models. The migration patterns had a spatially vertical structure, with the city development level being highly consistent with the flow intensity; for example, the first-level developments of Beijing, Shanghai, Chengdu, Guangzhou, Shenzhen, and Chongqing occupied a core position. A spatially horizontal structure was also formed, comprising 16 closely related city communities. Moreover, the quantified impact results indicated that migration pattern variation was significantly related to the population, value-added primary and secondary industry, the average wage, foreign capital, pension insurance, and certain aspects of unbalanced urban development. These findings can help policymakers to guide population migration, rationally allocate industrial infrastructure, and balance urban development.

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GeoSOT-Based Spatiotemporal Index of Massive Trajectory Data

Cited by 34 publications

References 28 publications

A low-altitude public air route network for UAV management constructed by global subdivision grids

A low-altitude public air route network for UAV management constructed by global subdivision grids

An Efficient Organization Method for Large-Scale and Long Time-Series Remote Sensing Data in a Cloud Computing Environment

Spatiotemporal Exploration of Chinese Spring Festival Population Flow Patterns and Their Determinants Based on Spatial Interaction Model

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