The research work has been seldom done about cloverleaf junction expression in a 3-dimensional city model (3DCM). The main reason is that the cloverleaf junction is often in a complex and enormous construction. Its ma...The research work has been seldom done about cloverleaf junction expression in a 3-dimensional city model (3DCM). The main reason is that the cloverleaf junction is often in a complex and enormous construction. Its main body is bestraddle in air,and has aerial intersections between its parts. This complex feature made cloverleaf junction quite different from buildings and terrain, therefore, it is difficult to express this kind of spatial objects in the same way as for buildings and terrain. In this paper,authors analyze spatial characteristics of cloverleaf junction, propose an all-constraint points TIN algorithm to partition cloverleaf junction road surface, and develop a method to visualize cloverleaf junction road surface using TIN. In order to manage cloverleaf junction data efficiently, the authors also analyzed the mechanism of 3DCM data management, extended BLOB type in relational database, and combined R-tree index to manage 3D spatial data. Based on this extension, an appropriate data展开更多
In this paper, we have preliminarily studied the application of ARGO (Arrayfor Real-time Geostrophic Oceanography) data to the Global Ocean Data Assimilation System ofNational Climate Center of China (NCC-GODAS), whic...In this paper, we have preliminarily studied the application of ARGO (Arrayfor Real-time Geostrophic Oceanography) data to the Global Ocean Data Assimilation System ofNational Climate Center of China (NCC-GODAS), which mainly contains 4 sub-systems such as datapreprocessing, real-time wind stress calculating, variational analysis and interpolating, and oceandynamic model. For the sake of using ARGO data, the relevant adjustment and improvement have beenmade at the corresponding aspects in the subsystems. Using the observation data from 1981 to 2003including the ARGO data of 2001 to July. 2003, we have performed a series of numerical experimentson this system. Comparing with the corresponding results of NCEP, It is illustrated that using ARGOdata can improve the results of NCC-GODAS in the region of the Middle Pacific, for instance SST,SSTA (SST anomalies), Nino index, sea sub-surface temperature, etc. Furthermore, it is obtained thatNCC-GODAS benefits from ARGO data in the other regions such as Atlantic Ocean, Indian Ocean, andextratropical Pacific Ocean much more than in the tropical Pacific.展开更多
文摘The research work has been seldom done about cloverleaf junction expression in a 3-dimensional city model (3DCM). The main reason is that the cloverleaf junction is often in a complex and enormous construction. Its main body is bestraddle in air,and has aerial intersections between its parts. This complex feature made cloverleaf junction quite different from buildings and terrain, therefore, it is difficult to express this kind of spatial objects in the same way as for buildings and terrain. In this paper,authors analyze spatial characteristics of cloverleaf junction, propose an all-constraint points TIN algorithm to partition cloverleaf junction road surface, and develop a method to visualize cloverleaf junction road surface using TIN. In order to manage cloverleaf junction data efficiently, the authors also analyzed the mechanism of 3DCM data management, extended BLOB type in relational database, and combined R-tree index to manage 3D spatial data. Based on this extension, an appropriate data
基金Supported by the National Natural Science Foundation of China under Grant No. 40231014.
文摘In this paper, we have preliminarily studied the application of ARGO (Arrayfor Real-time Geostrophic Oceanography) data to the Global Ocean Data Assimilation System ofNational Climate Center of China (NCC-GODAS), which mainly contains 4 sub-systems such as datapreprocessing, real-time wind stress calculating, variational analysis and interpolating, and oceandynamic model. For the sake of using ARGO data, the relevant adjustment and improvement have beenmade at the corresponding aspects in the subsystems. Using the observation data from 1981 to 2003including the ARGO data of 2001 to July. 2003, we have performed a series of numerical experimentson this system. Comparing with the corresponding results of NCEP, It is illustrated that using ARGOdata can improve the results of NCC-GODAS in the region of the Middle Pacific, for instance SST,SSTA (SST anomalies), Nino index, sea sub-surface temperature, etc. Furthermore, it is obtained thatNCC-GODAS benefits from ARGO data in the other regions such as Atlantic Ocean, Indian Ocean, andextratropical Pacific Ocean much more than in the tropical Pacific.
