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Modeling of Earth’s Gravity Fields Visualization Based on Quad Tree 被引量:2
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作者 LUO Zhicai LI Zhenhai ZHONG Bo 《Geo-Spatial Information Science》 2010年第3期216-220,共5页
The problems of the earth's gravity fields' visualization are both focus and puzzle currently. Aiming at multiresolution rendering, modeling of the Earth's gravity fields' data is discussed in the pape... The problems of the earth's gravity fields' visualization are both focus and puzzle currently. Aiming at multiresolution rendering, modeling of the Earth's gravity fields' data is discussed in the paper by using LOD algorithm based on Quad Tree. First, this paper employed the method of LOD based on Quad Tree to divide up the regional gravity anomaly data, introduced the combined node evaluation system that was composed of viewpoint related and roughness related systems, and then eliminated the T-cracks that appeared among the gravity anomaly data grids with different resolutions. The test results demonstrated that the gravity anomaly data grids' rendering effects were living, and the computational power was low. Therefore, the proposed algorithm was a suitable method for modeling the gravity anomaly data and has potential applications in visualization of the earth's gravity fields. 展开更多
关键词 LOD quad Tree earth’s gravity fields multiresolution rendering
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Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space
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作者 Ahmet SAYAR Suleyman EKEN Okan OZTURK 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2015年第2期98-108,共11页
We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) paraUelization and ... We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) paraUelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. The key challenge is how to balance the spatial processing load across a large number of worker nodes, given significant performance heterogeneity in nodes and processing skews in the workload. 展开更多
关键词 Kd tree quad tree Space partitioning Spatial indexing Range queries Query optimization
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