A Precise Urban Component Management Method Based on the GeoSOT Grid Code and BIM

Zhang, Huangchuang; Cheng, Chengqi; Miao, Shuangxi

doi:10.3390/ijgi8030159

Cited by 18 publications

(6 citation statements)

References 21 publications

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“…GeoSOT (Geographical coordinate grid Subdivision by One-dimension-integer and Two to n th power) subdivision theory ( Figure 1) proposed by Cheng, Tong, Chen, and Zhai (2016) has offered an efficient and scientific way of dividing the whole Earth seamlessly and overlappingly with multiple scales. Recently, it has been widely used and verified in spatial data management (Lu, Cheng, Jin, & Ma, 2013), urban component management (Zhang, Cheng, & Miao, 2019), massive trajectory data (Qian et al, 2019), remote-sensing image data organization (Wang, Cheng, Wu, Wu, & Teng, 2015), and other GIS applicational scenarios (Li, Pu, Cheng, & Chen, 2019). According to the GeoSOT subdivision theory, subdivision grids cover the complete Earth space without any leaks or overlaps.…”

Section: Geosot Grid Code Methodsmentioning

confidence: 99%

STGI：a spatio-temporal grid index model for marine big data

Wang

Jian

et al. 2020

Big Earth Data

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Marine big data are characterized by a large amount and complex structures, which bring great challenges to data management and retrieval. Based on the GeoSOT Grid Code and the composite index structure of the MongoDB database, this paper proposes a spatiotemporal grid index model (STGI) for efficient optimized query of marine big data. A spatio-temporal secondary index is created on the spatial code and time code columns to build a composite index in the MongoDB database used for the storage of massive marine data. Multiple comparative experiments demonstrate that the retrieval efficiency adopting the STGI approach is increased by more than two to three times compared with other index models. Through theoretical analysis and experimental verification, the conclusion could be achieved that the STGI model is quite suitable for retrieving large-scale spatial data with low time frequency, such as marine big data.

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Section: Geosot Grid Code Methodsmentioning

confidence: 99%

STGI：a spatio-temporal grid index model for marine big data

Wang

Jian

et al. 2020

Big Earth Data

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“…A conceptual model, Gen3DCity (Jaillot et al, 2021) generalizes these standards. Those standards were used by several works (Gaillard et al, 2015;Chen et al, 2018;Zhang et al;La Guardia et al) to integrate geometric data of one data model, either CityGML or IFC. Works like (Marnat et al, 2022) allow transforming the geometric data of heterogeneous data models to 3DTiles.…”

Section: Geometric Data Integrationmentioning

confidence: 99%

A model-driven methodology for integrating heterogeneous 3D geospatial urban entities

Colin,

Vinasco-Alvarez,

Samuel

et al. 2024

AGILE GIScience Ser.

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Abstract. Data on geospatial entities is increasingly available from various fields, such as GIS, CIM (City Information Modeling), and BIM (Building Information Modeling). They are described using different data models, such as IFC and CityGML, and are composed of both semantic and geometric data. Integrating this heterogeneous data to create a unified view of geospatial entities requires the use of technologies and methods adapted to each type of data. In this work, we propose a data integration methodology that leverages geospatial and semantic web technologies to provide data views suited to facilitating spatial and semantic navigation of these data. Concerning semantic data, we propose a model-driven data transformation process for limiting data loss during integration and reducing semantic heterogeneity between data from different urban information domains. For geometric data, we propose data transformations towards data formats for efficiently sharing, storing and visualizing 2D and 3D data. An open-source application is presented to illustrate this methodology.

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“…Land 2023, 12,1916 2 of 20 in geographic information systems, database management, and computer graphics [5][6][7]. The Geographical Grid Systems significantly enhance data organization, retrieval, and computational efficiency [8].…”

Section: Introductionmentioning

confidence: 99%

A Big Data Grided Organization and Management Method for Cropland Quality Evaluation

Miao,

Wang,

Huang

et al. 2023

Land

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A new gridded spatio-temporal big data fusion method is proposed for the organization and management of cropland big data, which could serve the analysis application of cropland quality evaluation and other analyses of geographic big data. Compared with traditional big data fusion methods, this method maps the spatio-temporal and attribute features of multi-source data to grid cells in order to achieve the structural unity and orderly organization of spatio-temporal big data with format differences, semantic ambiguities, and different coordinate projections. Firstly, this paper constructs a dissected cropland big data fusion model and completes the design of a conceptual model and logic model, constructs a cropland data organization model based on DGGS (discrete global grid system) and Hash coding, and realizes the unified management of vector data, raster data and text data by using multilevel grids. Secondly, this paper researches the evaluation methods of grid-scale adaptability, and generates distributed multilevel grid datasets to meet the needs of cropland area quality evaluation. Finally, typical data such as soil organic matter data, road network data, cropland area data, and statistic data in Da’an County, China, were selected to carry out the experiment. The experiment verifies that the method could not only realize the unified organization and efficient management of cultivated land big data with multimodal characteristics, but also support the evaluation of cropland quality.

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A Precise Urban Component Management Method Based on the GeoSOT Grid Code and BIM

Cited by 18 publications

References 21 publications

STGI：a spatio-temporal grid index model for marine big data

STGI：a spatio-temporal grid index model for marine big data

A model-driven methodology for integrating heterogeneous 3D geospatial urban entities

A Big Data Grided Organization and Management Method for Cropland Quality Evaluation

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