Search Results (7)

With the exponential increase in the volume of automatic dependent surveillance-broadcast (ADS-B), and other types of air traffic control (ATC) data containing spatiotemporal attributes, it remains uncertain how to respond to immediate ATC data access within a target area. Accordingly, an original multi-level disaggregated framework for airspace, and its corresponding information management is proposed. Further, a multi-scale grid modeling and coding mapping method of airspace information represented by ADS-B is put forth. Finally, tests on the validity of the 4D airspace-temporal grid we named as the GeoSOT-AS framework were conducted across key areas based on the development of an effective data organization method for ADS-B, or an effective algorithm for extracting relevant spatiotemporal data. Experimentally, it was demonstrated that GeoSOT-AS conforms to the existing Chinese specification of civil aeronautical charting and is advantageous for its low deformation and high practicality; furthermore, the airspace grid identification code modeling was less costly, and improved performance by >80% when used for ADS-B data extraction. GeoSOT-AS can thus provide effective reference and practical information for existing airspace data management methods represented by ADS-B and can subsequently be extended to other forms of airspace management scenarios. Full article

The construction of digital twin cities is a current research hotspot. Video data are one of the important aspects of digital twin cities, and their digital modeling is one of the important foundations of its construction. For this reason, the construction and digital analysis of video data space has become an urgent problem to be solved. After in-depth research, this study found that the existing video space construction methods have three shortcomings: first, the problem of high requirements for objective conditions or low accuracy; second, the lack of easy and efficient mapping algorithms from 2D video pixel coordinates to 3D; and third, the lack of efficient correlation mechanisms between video space and external geographic information, making it difficult to integrate video space with external information, and thus prevent a more effective analysis. In view of the above problems, this paper proposes a video stereo grid geometric space construction method based on GeoSOT-3D stereo grid coding and a camera imaging model to form a video stereo grid space model. Finally, targeted experiments of video stereo grid space geometry construction were conducted to analyze the experimental results before and after optimization and compare the variance size to verify the feasibility and effectiveness of the model. Full article

The integration analysis of multi-type geospatial information poses challenges to existing spatiotemporal data organization models and analysis models based on deep learning. For earthquake early warning, this study proposes a novel intelligent spatiotemporal grid model based on GeoSOT (SGMG-EEW) for feature fusion of multi-type geospatial data. This model includes a seismic grid sample model (SGSM) and a spatiotemporal grid model based on a three-dimensional group convolution neural network (3DGCNN-SGM). The SGSM solves the problem concerning that the layers of different data types cannot form an ensemble with a consistent data structure and transforms the grid representation of data into grid samples for deep learning. The 3DGCNN-SGM is the first application of group convolution in the deep learning of multi-source geographic information data. It avoids direct superposition calculation of data between different layers, which may negatively affect the deep learning analysis model results. In this study, taking the atmospheric temperature anomaly and historical earthquake precursory data from Japan as an example, an earthquake early warning verification experiment was conducted based on the proposed SGMG-EEW. Five groups of control experiments were designed, namely with the use of atmospheric temperature anomaly data only, use of historical earthquake data only, a non-group convolution control group, a support vector machine control group, and a seismic statistical analysis control group. The results showed that the proposed SGSM is not only compatible with the expression of a single type of spatiotemporal data but can also support multiple types of spatiotemporal data, forming a deep-learning-oriented data structure. Compared with the traditional deep learning model, the proposed 3DGCNN-SGM is more suitable for the integration analysis of multiple types of spatiotemporal data. Full article

As the amount of collected spatial information (2D/3D) increases, the real-time processing of these massive data is among the urgent issues that need to be dealt with. Discretizing the physical earth into a digital gridded earth and assigning an integral computable code to each grid has become an effective way to accelerate real-time processing. Researchers have proposed optimization algorithms for spatial calculations in specific scenarios. However, a complete set of algorithms for real-time processing using grid coding is still lacking. To address this issue, a carefully designed, integral grid-coding algebraic operation framework for GeoSOT-3D (a multilayer latitude and longitude grid model) is proposed. By converting traditional floating-point calculations based on latitude and longitude into binary operations, the complexity of the algorithm is greatly reduced. We then present the detailed algorithms that were designed, including basic operations, vector operations, code conversion operations, spatial operations, metric operations, topological relation operations, and set operations. To verify the feasibility and efficiency of the above algorithms, we developed an experimental platform using C++ language (including major algorithms, and more algorithms may be expanded in the future). Then, we generated random data and conducted experiments. The experimental results show that the computing framework is feasible and can significantly improve the efficiency of spatial processing. The algebraic operation framework is expected to support large geospatial data retrieval and analysis, and experience a revival, on top of parallel and distributed computing, in an era of large geospatial data. Full article

With the rapid development of large-scale satellite constellations and the increasing demand for rapid communication and emergency rescue using global satellite-based Internet, there have been new requirements for efficient algorithms for inter-communication between satellites. As the constellations of low-orbit satellites become larger, the complexities of real-time inter-satellite calculation and path planning are becoming more complicated and are increasing geometrically. To address the bottlenecks in large-scale node space computing, we introduced a global space grid. Based on this grid, an efficient calculation method of spatial inter-connection between satellite constellations is proposed, according to the concept of “storage for computing” and the high computational efficiency of the spatial grid model. This strategy includes the following parts: (1) the introduction of the GeoSOT-3D global grid model into aerospace and the construction of the aerospace grid indexing BigTable; (2) a set of algorithms for satellite visibility analysis according to the visible grid look-up table and the secondary grid index; and (3) planning inter-satellite routing by querying the grid’s inherent visibility. The idea at the basis of this method is to employ the “space for time” concept to convert the high-dimensional floating operations into one-dimensional matching operations by querying the inherent “visible” attribute of the grid. In our study, we simulated thousands of satellites, discretized their trajectories into grids, and pre-calculated the visibility between grid cells to plan the routing path for the ground data transmission. The theoretical analysis and experimental verification show that the algorithm is feasible and efficient, and it can significantly improve the computational efficiency of inter-satellite connection. We hope that the method can be used in emergency communications, disaster warning, and maritime rescue, and can contribute to the next generation of satellite internet and “satellite-ground” integrated networks. Full article

The increasing number of unmanned aerial vehicles (UAVs) has led to challenges related to solving the collision problem to ensure air traffic safety. The traditional approaches employed for collision detection suffer from two main drawbacks: first, the computational burden of a pairwise calculation increases exponentially with an increasing number of spatial entities; second, existing grid-based approaches are unsuitable for complicated scenarios with a large number of objects moving at high speeds. In the proposed model, we first identified UAVs and other spatial objects with GeoSOT-3D grids. Second, the nonrelational spatial database was initialized with a multitable strategy, and spatiotemporal data were inserted with the GeoSOT-3D grid codes as the primary key. Third, the collision detection procedure was transformed from a pairwise calculation to a multilevel query. Four simulation experiments were conducted to verify the feasibility and efficiency of the proposed collision detection model for UAVs in different environments. The results also indicated that 64 m GeoSOT-3D grids are the most suitable basic grid size, and the reduction in the time consumption compared with traditional methods reached approximately 50–80% in different scenarios. Full article

Currently, the rapid development of cities and the rapid increase in urban populations have led to a sharp increase in urban components, making precise urban component management, query efficiency, and operational visualization urgent problems to be solved. In this paper, an in-depth study is carried out, pointing out that the current two-dimensional map or component management method based on a real-life three-dimensional city has defects, including query difficulty, fuzzy management, and inefficiency, and it is impossible to accurately and efficiently manage urban components. Then, this paper uses a combination of GIS technology and BIM technology as the starting point. On one hand, this combined technology is based on the high efficiency of the underlying data organization of the GeoSOT grid code and the accuracy of real geographic location expression; on the other hand, based on the integrity of the building information representation and the accuracy of the relative position of internal components of BIM, a precise urban component management method based on GeoSOT grid code and BIM is proposed. Finally, based on this method, a real-time 3D Earth visualization platform is established by using the Cesium platform. Taking the fire hydrant component management of the commercial Guanlan Street in Baiyin City, Gansu Province, China as an example, the precise management of the components in this area is realized, which proves that the method can achieve precise urban component management. Full article