Assessing the state of the art in Discrete Global Grid Systems: OGC criteria and present functionality

GEOMATICA ◽  
2020 ◽  
Vol 74 (1) ◽  
pp. 9-30 ◽  
Author(s):  
Ben Bondaruk ◽  
Steven A. Roberts ◽  
Colin Robertson
Keyword(s):  
Data Structures ◽  
Spatial Data ◽  
Theoretical Development ◽  
Continuous Growth ◽  
Grid Systems ◽  
Spatial Features ◽  
Potential Applications ◽  
Software Implementations ◽  
Global Grid ◽  
Integration Analysis

The continuous growth of available geospatial data requires new methods for its integration, analysis, and visualization to be explored and implemented in software available to the geospatial community. Discrete Global Grid Systems (DGGS) are an emerging method for spatial data handling in the digital earth framework. DGGS are hierarchical data structures for discretizing the Earth’s surface that have seen considerable theoretical development over the last two decades. In this paper, four software implementations are reviewed, dggridR, H3, OpenEAGGR, and S2, to explore their potential applications in data modelling and GIS, as well as their performance. These software implementations were also evaluated against the recently published Open Geospatial Consortium (OGC) abstract specification. The results indicate great potential and versatility for utilizing such systems in geospatial analysis, if basic methods for converting and handling spatial features are further developed. The performance of these systems is shown to be highly scalable and operational with datasets of various sizes. Yet, it is demonstrated that the current software implementations generally fall short of fulfilling all of the OGC requirements or it was not possible to confirm their compliance. The assessment here identified that further enhancements, endorsement of OGC criteria, and their explicit acknowledgment within official documentation remain key research needs for the evaluated software packages. Further work developing operational DGGS that solve real world problems may promote greater community adoption and integration of DGGS data structures into commonly used geospatial platforms.

scholarly journals THE TRANSFORM BETWEEN GEOGRAPHIC COORDINATES AND LOCATION CODES OF APERTURE 4 HEXAGONAL GRID SYSTEM

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 161-167 ◽  
Author(s):  
R. Wang ◽  
J. Ben ◽  
Y. Li ◽  
L. Du
Keyword(s):  
Spatial Data ◽  
Data Model ◽  
Geospatial Data ◽  
Grid System ◽  
Hexagonal Grid ◽  
Encoding Scheme ◽  
Global System ◽  
Grid Systems ◽  
Grid Codes ◽  
Global Grid

Discrete global grid system is a new data model which supports the fusion processing of multi-source geospatial data. In discrete global grid systems, all cell operations can be completed by codes theoretically, but most of current spatial data are in the forms of geographic coordinates and projected coordinates. It is necessary to study the transform between geographic coordinates and grid codes, which will support data entering and getting out of the systems. This paper chooses the icosahedral hexagonal discrete global system as a base, and builds the mapping relationships between the sphere and the icosahedron. Then an encoding scheme of planar aperture 4 hexagonal grid system is designed and applied to the icosahedron. Basing on this, a new algorithm of transforms between geographic coordinates and grid codes is designed. Finally, experiments test the accuracy and efficiency of this algorithm. The efficiency of code addition of HLQT is about 5 times the efficiency of code addition of HQBS.

scholarly journals Development of Multilayer-Based Map Matching to Enhance Performance in Large Truck Fleet Dispatching

2021 ◽  
Vol 10 (2) ◽  
pp. 79
Author(s):  
Ching-Yun Mu ◽  
Tien-Yin Chou ◽  
Thanh Van Hoang ◽  
Pin Kung ◽  
Yao-Min Fang ◽  
...  
Keyword(s):  
Data Structures ◽  
Spatial Data ◽  
Spatial Information ◽  
Data Retrieval ◽  
Spatial Data Mining ◽  
Map Matching ◽  
Matching Algorithm ◽  
Table Method ◽  
Look Up Table ◽  
The Look

Spatial information technology has been widely used for vehicles in general and for fleet management. Many studies have focused on improving vehicle positioning accuracy, although few studies have focused on efficiency improvements for managing large truck fleets in the context of the current complex network of roads. Therefore, this paper proposes a multilayer-based map matching algorithm with different spatial data structures to deal rapidly with large amounts of coordinate data. Using the dimension reduction technique, the geodesic coordinates can be transformed into plane coordinates. This study provides multiple layer grouping combinations to deal with complex road networks. We integrated these techniques and employed a puncture method to process the geometric computation with spatial data-mining approaches. We constructed a spatial division index and combined this with the puncture method, which improves the efficiency of the system and can enhance data retrieval efficiency for large truck fleet dispatching. This paper also used a multilayer-based map matching algorithm with raster data structures. Comparing the results revealed that the look-up table method offers the best outcome. The proposed multilayer-based map matching algorithm using the look-up table method is suited to obtaining competitive performance in identifying efficiency improvements for large truck fleet dispatching.

scholarly journals Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling

2020 ◽  
Vol 1 ◽  
pp. 1-23
Author(s):  
Majid Hojati ◽  
Colin Robertson
Keyword(s):  
Big Data ◽  
Spatial Analysis ◽  
Cellular Automata ◽  
Spatial Data ◽  
Data Model ◽  
Data Access ◽  
Environmental Modeling ◽  
Modeling Framework ◽  
Global Grid

Abstract. With new forms of digital spatial data driving new applications for monitoring and understanding environmental change, there are growing demands on traditional GIS tools for spatial data storage, management and processing. Discrete Global Grid System (DGGS) are methods to tessellate globe into multiresolution grids, which represent a global spatial fabric capable of storing heterogeneous spatial data, and improved performance in data access, retrieval, and analysis. While DGGS-based GIS may hold potential for next-generation big data GIS platforms, few of studies have tried to implement them as a framework for operational spatial analysis. Cellular Automata (CA) is a classic dynamic modeling framework which has been used with traditional raster data model for various environmental modeling such as wildfire modeling, urban expansion modeling and so on. The main objectives of this paper are to (i) investigate the possibility of using DGGS for running dynamic spatial analysis, (ii) evaluate CA as a generic data model for dynamic phenomena modeling within a DGGS data model and (iii) evaluate an in-database approach for CA modelling. To do so, a case study into wildfire spread modelling is developed. Results demonstrate that using a DGGS data model not only provides the ability to integrate different data sources, but also provides a framework to do spatial analysis without using geometry-based analysis. This results in a simplified architecture and common spatial fabric to support development of a wide array of spatial algorithms. While considerable work remains to be done, CA modelling within a DGGS-based GIS is a robust and flexible modelling framework for big-data GIS analysis in an environmental monitoring context.

Emotional and Subjective Volunteered Geographical Information

2017 ◽  
pp. 97-112 ◽  
Author(s):  
Jiri Panek
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Spatial Data ◽  
Large Scale ◽  
Geographical Information ◽  
Emotional Information ◽  
Spatial Features ◽  
Spatial Locations ◽  
The City

Crowdsroucing of emotional information can take many forms, from social networks data mining to large-scale surveys. The author presents the case-study of emotional mapping in Ostrava´s district Ostrava-Poruba, Czech Republic. Together with the local administration, the author crowdsourced the emotional perceptions of the location from almost 400 citizens, who created 4,051 spatial features. Additional to the spatial data there were 1,244 comments and suggestions for improvements in the district. Furthermore, the author is looking for patterns and hot-spots within the city and if there are any relevant linkages between certain emotions and spatial locations within the city.

scholarly journals Indexing Mixed Aperture Icosahedral Hexagonal Discrete Global Grid Systems

2020 ◽  
Vol 9 (3) ◽  
pp. 171 ◽  
Author(s):  
Rui Wang ◽  
Jin Ben ◽  
Jianbin Zhou ◽  
Mingyang Zheng
Keyword(s):  
3D Model ◽  
Spherical Geometry ◽  
Grid Structure ◽  
Generation Efficiency ◽  
Grid Systems ◽  
Indexing Method ◽  
Data Volume ◽  
Global Grid ◽  
Spherical Vector

Discrete global grid systems (DGGSs) are an emerging multiresolution 3D model used to integrate and analyze big earth data. The characteristic of multiresolution is usually realized by hierarchically subdividing cells on the sphere using certain refinement. This paper introduces mixed aperture three- and four- icosahedral hexagonal DGGSs using two types of refinement, the various combinations of which can provide more resolutions compared with pure aperture hexagonal DGGSs and can flexibly design the aperture sequence according to the target resolutions. A general hierarchy-based indexing method is first designed, and related indexing arithmetics and algorithm are developed based on the indexing method. Then, the grid structure on the surface of the icosahedron is described and by projection spherical grids are obtained. Experiments show that the proposed scheme is superior to pure aperture schemes in choosing grid resolutions and can reduce the data volume by 38.5% in representing 1-km resolution raster dataset; using the proposed indexing arithmetics to replace spherical geometry operations in generating discrete spherical vector lines based on hexagonal cells can improve the generation efficiency.

scholarly journals General Method for Extending Discrete Global Grid Systems to Three Dimensions

2020 ◽  
Vol 9 (4) ◽  
pp. 233 ◽  
Author(s):  
Benjamin Ulmer ◽  
John Hall ◽  
Faramarz Samavati
Keyword(s):  
Three Dimensional ◽  
Use Cases ◽  
Three Dimensions ◽  
Grid Systems ◽  
3D Data ◽  
Third Dimension ◽  
2D And 3D ◽  
Polyhedral Projection ◽  
Global Grid ◽  
General Method

Geospatial sensors are generating increasing amounts of three-dimensional (3D) data. While Discrete Global Grid Systems (DGGS) are a useful tool for integrating geospatial data, they provide no native support for 3D data. Several different 3D global grids have been proposed; however, these approaches are not consistent with state-of-the-art DGGSs. In this paper, we propose a general method that can extend any DGGS to the third dimension to operate as a 3D DGGS. This extension is done carefully to ensure any valid DGGS can be supported, including all refinement factors and non-congruent refinement. We define encoding, decoding, and indexing operations in a way that splits responsibility between the surface DGGS and the 3D component, which allows for easy transference of data between the 2D and 3D versions of a DGGS. As a part of this, we use radial mapping functions that serve a similar purpose as polyhedral projection in a conventional DGGS. We validate our method by creating three different 3D DGGSs tailored for three specific use cases. These use cases demonstrate our ability to quickly generate 3D global grids while achieving desired properties such as support for large ranges of altitudes, volume preservation between cells, and custom cell aspect ratio.

Sign in / Sign up

Export Citation Format

Share Document