The OGC® Discrete Global Grid System core standard: A framework for rapid geospatial integration

Purss, Matthew B.J.; Gibb, Robert; Samavati, Faramarz; Peterson, Perry; Ben, Jianwei

doi:10.1109/igarss.2016.7729935

Cited by 34 publications

(18 citation statements)

References 10 publications

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“…Discrete Grid Global System (DGGS) is a spatial reference system that describes a position in the real world by a datum [4]. Two geospatial standard organizations of the Open Geo Consortium (OGC) and the International Organization for Standardization Technical Committees (ISO/TC) 211 are promoting DGGS as a new framework for coordinate conversion from an ellipsoidal coordinate system to a plane.…”

Section: A Discrete Global Grid System (Dggs)mentioning

confidence: 99%

“…These irregular sizes of the grid can be a problem of the projection and the seamless integration from various geospatial data sources. In order to solve the problem, the Discrete Grid Global System (DGGS) has recently been proposed for geo-referencing [4]. DGGS divides the Earths surface into grids with multiple levels of granularity and generates a code per each grid through a SFC [5], [6].…”

Section: Introductionmentioning

confidence: 99%

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Efficient Encoding and Decoding Extended Geocodes for Massive Point Cloud Data

Kim¹,

Kim²,

Lee³

et al. 2019

EasyChair Preprints

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With the development of mobile surveying and mapping technologies, point cloud data has been emerging in a variety of applications including robot navigation, self-driving drones/vehicles, and three-dimensional (3D) urban space modeling. In addition, there is an increasing demand for the database management system to share and reuse point cloud data, unlike being treated as archive files in the traditional uses and applications. However, database scalability needs to be explored to process and manage a massive volume of point cloud data defined by a 3D (X, Y, and Z) coordinates system.  The typical approach to handle big data and distribute it across multiple nodes is data partitioning.~Geohashing is a popular way to convert a latitude/longitude spatial point into a code/string and has used for storing data into buckets of the grid. Many methods of handling big geospatial data, especially NoSQL databases, are based on the geohashing techniques. In this paper, we propose an efficient method to encode/decode 3D point cloud in a Discrete Global Grid System (DGGS) that represents the Earth as hierarchical sequences of equal area/volume tessellations, similar to geohash. The current geohash of base36 has the difficulties of working with high-resolution 3D point clouds for data storage, filter, integration, and analytics because of its limitation of cell size and unequal areas. We employ DGGS-based Morton codes with more than 64 bits for precise 3D coordinates of point cloud and compare the encoding/decoding performance between two implementations: using strings and using the combination of bit interleaving and lookup tables.

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Section: A Discrete Global Grid System (Dggs)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient Encoding and Decoding Extended Geocodes for Massive Point Cloud Data

Kim¹,

Kim²,

Lee³

et al. 2019

EasyChair Preprints

View full text Add to dashboard Cite

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“…The global distribution of spatial vector data will push data management into a global scale in the era of big data. Discrete Global Grid Systems (DGGS), a new OGC standard, is to meet the needs for global sampling, storage, modeling, processing, analysis, and visualization (Purss, Gibb, Samavati, Peterson, & Ben, 2016). The modeling and expressing of big spatial vector data (BSVD) in DGGS is difficult because of its differences and continuous (Tong et al, 2013).…”

Section: Dggsmentioning

confidence: 99%

Big spatial vector data management: a review

Yao

2018

Big Earth Data

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Spatial vector data with high-precision and wide-coverage has exploded globally, such as land cover, social media, and other datasets, which provides a good opportunity to enhance the national macroscopic decision-making, social supervision, public services, and emergency capabilities. Simultaneously, it also brings great challenges in management technology for big spatial vector data (BSVD). In recent years, a large number of new concepts, parallel algorithms, processing tools, platforms, and applications have been proposed and developed to improve the value of BSVD from both academia and industry. To better understand BSVD and take advantage of its value effectively, this paper presents a review that surveys recent studies and research work in the data management field for BSVD. In this paper, we discuss and itemize this topic from three aspects according to different information technical levels of big spatial vector data management. It aims to help interested readers to learn about the latest research advances and choose the most suitable big data technologies and approaches depending on their system architectures. To support them more fully, firstly, we identify new concepts and ideas from numerous scholars about geographic information system to focus on BSVD scope in the big data era. Then, we conclude systematically not only the most recent published literatures but also a global view of main spatial technologies of BSVD, including data storage and organization, spatial index, processing methods, and spatial analysis. Finally, based on the above commentary and related work, several opportunities and challenges are listed as the future research interests and directions for reference.

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“…A DGGs can be thought of as a framework of Digital Earth [5] for the integration of spatial data [6,7] and earth system modeling [8]. In order to realize the grid representation of geographical objects, integration of vector features, that is, the discretization of vector features into grid cells of corresponding scales according to certain criteria, must be performed and is the core problem of discrete global grid systems research [9].…”

Section: Introductionmentioning

confidence: 99%

A Topology Preserving Gridding Method for Vector Features in Discrete Global Grid Systems

Zhou

Lian

Zhang

et al. 2020

IJGI

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Topological distortion seriously affects spatial cognition. To solve this problem caused by the integration of vector features in discrete global grid systems (DGGs), a topology-preserving gridding method for vector features is proposed. The method proposed determines the topological distortion according to the relationship between grid cells and then increases the local resolution of vector features by employing the multi-level resolution characteristic of DGGs, to repair three kinds of topological distortions. Experimental results show that the proposed method can effectively maintain the topological relationship between the original vector features, and the amount of data is stable, thus ensuring the correct integration of vector features in the DGGs.

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The OGC® Discrete Global Grid System core standard: A framework for rapid geospatial integration

Cited by 34 publications

References 10 publications

Efficient Encoding and Decoding Extended Geocodes for Massive Point Cloud Data

Efficient Encoding and Decoding Extended Geocodes for Massive Point Cloud Data

Big spatial vector data management: a review

A Topology Preserving Gridding Method for Vector Features in Discrete Global Grid Systems

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