Geological tetrahedral model-oriented hybrid spatial indexing structure based on Octree and 3D R*-tree

Wang, Yongzhi; Lv, Hua; Ma, Yuqing

doi:10.1007/s12517-020-05752-6

Cited by 11 publications

(6 citation statements)

References 23 publications

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“…To overcome the shortcoming of single index methods, more and more scholars try to design hybrid index technology. Some proposed strategies are combining with different index structures organically and achieve a better performance in query operation [9,11,[16][17][18][19].…”

Section: Hybrid Indexing Structurementioning

confidence: 99%

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A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree

Wang

Zhang

et al. 2021

Applied Sciences

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The spatial index structure is one of the most important research topics for organizing and managing massive 3D Point Cloud. As a point in Point Cloud consists of Cartesian coordinates (x,y,z), the common method to explore geometric information and features is nearest neighbor searching. An efficient spatial indexing structure directly affects the speed of the nearest neighbor search. Octree and kd-tree are the most used for Point Cloud data. However, Octree or KD-tree do not perform best in nearest neighbor searching. A highly balanced tree, 3D R*-tree is considered the most effective method so far. So, a hybrid spatial indexing structure is proposed based on Octree and 3D R*-tree. In this paper, we discussed how thresholds influence the performance of nearest neighbor searching and constructing the tree. Finally, an adaptive way method adopted to set thresholds. Furthermore, we obtained a better performance in tree construction and nearest neighbor searching than Octree and 3D R*-tree.

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Section: Hybrid Indexing Structurementioning

confidence: 99%

“…So, many hybrid index methods are proposed in recent years. Such as combining 3D R*-tree and kd-tree [18], octree and 3D R*-tree [19], quad-tree and 3D R-tree [31], kd-tree and octree [11], octree and kd-tree [3,34], quad-tree and octree [35], etc. The main idea is to improve the imbalance of tree and speed up the query operation.…”

Section: D R*-treementioning

confidence: 99%

A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree

Wang

Zhang

et al. 2021

Applied Sciences

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“…The first aspect is the 3D geologic model building algorithm. Traditional 3D geological models can be classified into the octree model (Wang et al, 2020), triangular prism (Zhang et al, 2015), TEN model (He et al, 2022), and TIN model (Ouyang et al, 2023). In addition, among the equivalence surface algorithms are the Cuberille algorithm proposed by Herman and Liu (1979), the Marching cube algorithm proposed by Lorensen and Cline (1987), and the decomposition cube method proposed by Cline et al (1988).…”

Section: Introductionmentioning

confidence: 99%

Research and application of urban 3D geologic modeling technology based on multivariate complex geologic structures——Take Chengdu as an example

Hao,

Zhang,

Zhan

et al. 2024

Preprint

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Three-dimensional (3D) geological models can visually present various underground geological body forms, geological structures, geological hazards, which is of great significance for urban spatial planning and urban geological hazard prevention and control. To overcome technical difficulties such as poor accuracy, poor aesthetics and the difficulty to modify and improve the model afterwards, the 3D model of urban geology under complex geological conditions was constructed. This paper proposes a 3D modeling technology for urban geology with multiple complex geological structures based on multi-source heterogeneous data with the common constraints of geological priori knowledge and geological laws. This technique can utilize various modeling data, such as DEM data, planimetric geological maps, comprehensive geological profiles, borehole data, geophysical interpretation data and tectonic outline maps. Under the common constraints of geological prior knowledge and geological laws, the block modeling technique is used to complete the construction of 3D urban geological models under complex geological conditions. Taking the construction of 3D geological model in Chengdu as an example, this paper focuses on the theory and algorithm of 3D modeling of urban geology, the geological background of the demonstration area, the preparation and pre-processing of 3D modeling data, and the research and demonstration application of 3D modeling technology for urban geology. The construction of a 3D geological model of Chengdu was completed using a 3D modeling technology of a multi-complex urban geological structure.

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“…Our objective is to support arbitrary geospatial partitioning algorithms, which can handle the needs of applications that require different levels of granularity in terms of location reporting. Spatial indexing [9,31,32] is a common approach used for partitioning, and numerous techniques have been proposed that partition the data domain according to varying criteria, such as area, perimeter, data point count, etc. We build upon existing spatial indexing techniques, and adapt the partition criteria to account for the specific goals of fairness.…”

Section: Introductionmentioning

confidence: 99%

Fair Spatial Indexing: A paradigm for Group Spatial Fairness

Shaham¹,

Ghinita²,

Shahabi³

2023

Preprint

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Machine learning (ML) is playing an increasing role in decisionmaking tasks that directly affect individuals, e.g., loan approvals, or job applicant screening. Significant concerns arise that, without special provisions, individuals from under-privileged backgrounds may not get equitable access to services and opportunities. Existing research studies fairness with respect to protected attributes such as gender, race or income, but the impact of location data on fairness has been largely overlooked. With the widespread adoption of mobile apps, geospatial attributes are increasingly used in ML, and their potential to introduce unfair bias is significant, given their high correlation with protected attributes. We propose techniques to mitigate location bias in machine learning. Specifically, we consider the issue of miscalibration when dealing with geospatial attributes. We focus on spatial group fairness and we propose a spatial indexing algorithm that accounts for fairness. Our KD-tree inspired approach significantly improves fairness while maintaining high learning accuracy, as shown by extensive experimental results on real data.

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Geological tetrahedral model-oriented hybrid spatial indexing structure based on Octree and 3D R*-tree

Cited by 11 publications

References 23 publications

A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree

A Hybrid Spatial Indexing Structure of Massive Point Cloud Based on Octree and 3D R*-Tree

Research and application of urban 3D geologic modeling technology based on multivariate complex geologic structures——Take Chengdu as an example

Fair Spatial Indexing: A paradigm for Group Spatial Fairness

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