Categorization and Conversions for Indexing Methods of Discrete Global Grid Systems

Amiri, Ali Mahdavi; Samavati, Faramarz; Peterson, Perry

doi:10.3390/ijgi4010320

Cited by 58 publications

(29 citation statements)

References 26 publications

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“…Google Earth is becoming a convenient platform for integrating and sharing the data and research findings of scientists from many disciplines at the global scale [11,22,[30][31][32][33][34][35][36]. In this paper, we have designed a systematic framework to visualize and disseminate the structure of the Earth's lithosphere on Google Earth in an intuitive 3D global perspective.…”

Section: Resultsmentioning

confidence: 99%

Visualizing the Structure of the Earth’s Lithosphere on the Google Earth Virtual-Globe Platform

Zhu

Kan

Zhang

et al. 2016

IJGI

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While many of the current methods for representing the existing global lithospheric models are suitable for academic investigators to conduct professional geological and geophysical research, they are not suited to visualize and disseminate the lithospheric information to non-geological users (such as atmospheric scientists, educators, policy-makers, and even the general public) as they rely on dedicated computer programs or systems to read and work with the models. This shortcoming has become more obvious as more and more people from both academic and non-academic institutions struggle to understand the structure and composition of the Earth's lithosphere. Google Earth and the concomitant Keyhole Markup Language (KML) provide a universal and user-friendly platform to represent, disseminate, and visualize the existing lithospheric models. We present a systematic framework to visualize and disseminate the structure of the Earth's lithosphere on Google Earth. A KML generator is developed to convert lithospheric information derived from the global lithospheric model LITHO1.0 into KML-formatted models, and a web application is deployed to disseminate and visualize those models on the Internet. The presented framework and associated implementations can be easily exported for application to support interactively integrating and visualizing the internal structure of the Earth with a global perspective.

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Section: Resultsmentioning

confidence: 99%

Visualizing the Structure of the Earth’s Lithosphere on the Google Earth Virtual-Globe Platform

Zhu

Kan

Zhang

et al. 2016

IJGI

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“…If, in the t-and b-directions, the k th level of the World Wind digital Earth grid can be obtained by aggregating the k1 th level of the GeoSOT grid, the two grids must satisfy Equation (9). Equation (18) can be obtained from Equations (12) and (17):…”

Section: Analysis Of the Isomorphism Between Geosot And Existing Digimentioning

confidence: 99%

“…R lat R long = n lat , n long R basic R basic (9) To ensure the effectiveness of the consistent grid, R basic should be the largest grid that can be aggregated into other types of latitude and longitude grids. For example, the national basic map scale 1:1,000,000 (without considering combined maps) constitutes an equal latitude and longitude grid with an interval of 4 • in latitude and 6 • in longitude.…”

Section: Constraints For Constructing Consistent Latitude and Longitumentioning

confidence: 99%

“…No unified subdivision grid for information exchange and comprehensive application has been developed. A few efforts have been made recently on the hierarchical grid conversion along with the indexing methods [9,14]; however, the subdivision methods do not adapt to the existing geographical data in all types of applications, and the indexing efficiency needs further enhancement. Therefore, a globally consistent spatial information subdivision grid model that is compatible with most of the existing subdivision grid systems is needed.…”

Section: Introductionmentioning

confidence: 99%

“…Subdivision grids can be categorized according to their geometry into subdivision grids based on the latitude and longitude grid [1][2][3], those based on coordinate grids [4,5], polygonal subdivision grids based on polyhedrons [6][7][8][9], irregular and mixed subdivision grids [10], etc. According to spatial information service industries, grids are categorized into basic geographical information grids, worldwide reference systems (WRSs) or grid reference systems (GRSs) for remote satellite systems, navigation and positioning grids, etc.…”

Section: Introductionmentioning

confidence: 99%

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A Subdivision Method to Unify the Existing Latitude and Longitude Grids

Cheng

Tong

Chen

et al. 2016

IJGI

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Abstract:As research on large regions of earth progresses, many geographical subdivision grids have been established for various spatial applications by different industries and disciplines. However, there is no clear relationship between the different grids and no consistent spatial reference grid that allows for information exchange and comprehensive application. Sharing and exchange of data across departments and applications are still at a bottleneck. It would represent a significant step forward to build a new grid model that is inclusive of or compatible with most of the existing geodesic grids and that could support consolidation and exchange within existing data services. This study designs a new geographical coordinate global subdividing grid with one dimension integer coding on a 2 n tree (GeoSOT) that has 2 n coordinate subdivision characteristics (global longitude and latitude subdivision) and can form integer hierarchies at degree, minute, and second levels. This grid has the multi-dimensional quadtree hierarchical characteristics of a digital earth grid, but also provides good consistency with applied grids, such as those used in mapping, meteorology, oceanography and national geographical, and three-dimensional digital earth grids. No other existing grid codes possess these characteristics.

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Discrete Global Grid Systems

Peterson

2017

International Encyclopedia of Geography

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Discrete global grid systems (DGGS) are spatial references that use a hierarchical tessellation of cells to partition and address the entire globe. DGGS are designed to portray real‐world phenomena by synthesizing digital values on a common discrete geospatial data structure. DGGS provide an organizational structure that permits fast integration between multiple sources of large and variable geospatial data sources sufficient for fast web‐based visualization and analysis. They are commonly used to create virtual globes. The adoption of an optimized DGGS is considered a favorable choice for the establishment of distributed Digital Earth information systems. A DGGS is designed to be an information grid, not a navigation grid. DGGS provide a reference frame for repeating the location of measured earth observations, feature interpretations, and extrapolated predictions. Information integration, decomposition, and aggregation can be optimized in the hierarchical structure, which can be exploited to support data processing, storage, discovery, transmission, visualization, computation, analysis, and modeling.

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Categorization and Conversions for Indexing Methods of Discrete Global Grid Systems

Cited by 58 publications

References 26 publications

Visualizing the Structure of the Earth’s Lithosphere on the Google Earth Virtual-Globe Platform

Visualizing the Structure of the Earth’s Lithosphere on the Google Earth Virtual-Globe Platform

A Subdivision Method to Unify the Existing Latitude and Longitude Grids

Discrete Global Grid Systems

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