Special Issue "GIS Software and Engineering for Big Data"

Special Issue Editors

Prof. Dr. Peng Yue
E-Mail Website
Guest Editor
School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan, Hubei, 430079, China
Interests: Earth science data and information systems, GIS, Data science, Semantics, Cloud computing
Special Issues and Collections in MDPI journals
Prof. Dr. Danielle Ziebelin
E-Mail Website
Guest Editor
STEAMER group, LIG, Universite Grenoble Alpes - UGA, LIG - Bâtiment IMAG - CS 40700 - 38058 GRENOBLE CEDEX, France
Interests: GIS, Knowledge representation and reasoning, Problem solving systems, Semantic web, Ontologies, Spatio-temporal reasoning, Data integration
Dr. Yaxing Wei
E-Mail Website
Guest Editor
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, P.O. Box 2008, MS - 6290 Oak Ridge, TN 37831 – 6290, USA
Interests: Geospatial data management and systems, Geospatial standards and interoperability; Web GIS, Geospatial information analysis, Geospatial services

Special Issue Information

Dear Colleagues,

The increasing spread and usage of big data is changing the way data are managed and analyzed. The capabilities of traditional GIS (geographical information system) software are often limited in dealing with big data challenges, such as versatile data forms, steaming processing, large scale parallel computing, and dynamic mapping and visualization. Significant improvements are needed in innovative software development and engineering applications of GIS. First, GIS needs to be extended to accommodate dynamic observations of sensors including volunteered geographic information (VGI). Second, new data models and indexing algorithms are needed to store and access unstructured, multidimensional, and dynamic data. Third, the computing paradigm calls for innovation to meet the demands of stream processing, real-time analysis, and information extraction from large-scale datasets. Fourth, novel methods in mapping and visualization shall be studied to dynamically display, analyze, and simulate geographical phenomena and their progresses. Finally, data mining and analysis technologies for big geospatial data deserve further research to perform data, information, and knowledge transformations.

As a result, the GIS software and engineering domain has seen increasing applications for advanced information technologies, such as the map/reduce computing paradigm, stream processing, NoSQL/NewSQL, block chain, and artificial intelligence technologies. This Special Issue intends to collect the latest and future directions in GIS software development and engineering applications to deal with spatio-temporal big data. We invite authors to submit their original papers. Potential topics include, but are not limited to:

  • Data and computational architecture of GIS
  • Internet of Things and sensor observations in GIS
  • High-performance geo-computation and geo-stream processing
  • Geospatial data model and data cube
  • Workflow and provenance
  • Distributed and scalable geospatial database
  • Web GIS and geospatial services
  • Virtual reality (VR) and augmented reality(AR) GIS
  • Spatio-temporal big data visualization
  • Knowledge representation in GIS
  • Artificial intelligence in GIS
  • Block chain for GIS
  • GIS tools and applications for big data

Prof. Dr. Peng Yue
Prof. Dr. Danielle Ziebelin
Dr. Yaxing Wei
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Software architecture
  • Computational architecture
  • Distributed geoprocessing
  • Parallel geo-computation
  • Geospatial database
  • AR/VR GIS
  • Cloud GIS
  • Geospatial artificial intelligence
  • Geospatial block chain
  • Big data GIS applications

Published Papers (2 papers)

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Research

Open AccessArticle
A Universal Generating Algorithm of the Polyhedral Discrete Grid Based on Unit Duplication
ISPRS Int. J. Geo-Inf. 2019, 8(3), 146; https://doi.org/10.3390/ijgi8030146 - 19 Mar 2019
Cited by 1
Abstract
Based on the analysis of the problems in the generation algorithm of discrete grid systems domestically and abroad, a new universal algorithm for the unit duplication of a polyhedral discrete grid is proposed, and its core is “simple unit replication + effective region [...] Read more.
Based on the analysis of the problems in the generation algorithm of discrete grid systems domestically and abroad, a new universal algorithm for the unit duplication of a polyhedral discrete grid is proposed, and its core is “simple unit replication + effective region restriction”. First, the grid coordinate system and the corresponding spatial rectangular coordinate system are established to determine the rectangular coordinates of any grid cell node. Then, the type of the subdivision grid system to be calculated is determined to identify the three key factors affecting the grid types, which are the position of the starting point, the length of the starting edge, and the direction of the starting edge. On this basis, the effective boundary of a multiscale grid can be determined and the grid coordinates of a multiscale grid can be obtained. A one-to-one correspondence between the multiscale grids and subdivision types can be established. Through the appropriate rotation, translation and scaling of the multiscale grid, the node coordinates of a single triangular grid system are calculated, and the relationships between the nodes of different levels are established. Finally, this paper takes a hexagonal grid as an example to carry out the experiment verifications by converting a single triangular grid system (plane) directly to a single triangular grid with a positive icosahedral surface to generate a positive icosahedral surface grid. The experimental results show that the algorithm has good universality and can generate the multiscale grid of an arbitrary grid configuration by adjusting the corresponding starting transformation parameters. Full article
(This article belongs to the Special Issue GIS Software and Engineering for Big Data)
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Open AccessArticle
Interactive and Online Buffer-Overlay Analytics of Large-Scale Spatial Data
ISPRS Int. J. Geo-Inf. 2019, 8(1), 21; https://doi.org/10.3390/ijgi8010021 - 10 Jan 2019
Abstract
Buffer and overlay analysis are fundamental operations which are widely used in Geographic Information Systems (GIS) for resource allocation, land planning, and other relevant fields. Real-time buffer and overlay analysis for large-scale spatial data remains a challenging problem because the computational scales of [...] Read more.
Buffer and overlay analysis are fundamental operations which are widely used in Geographic Information Systems (GIS) for resource allocation, land planning, and other relevant fields. Real-time buffer and overlay analysis for large-scale spatial data remains a challenging problem because the computational scales of conventional data-oriented methods expand rapidly with data volumes. In this paper, we present HiBO, a visualization-oriented buffer-overlay analysis model which is less sensitive to data volumes. In HiBO, the core task is to determine the value of pixels for display. Therefore, we introduce an efficient spatial-index-based buffer generation method and an effective set-transformation-based overlay optimization method. Moreover, we propose a fully optimized hybrid-parallel processing architecture to ensure the real-time capability of HiBO. Experiments on real-world datasets show that our approach is capable of handling ten-million-scale spatial data in real time. An online demonstration of HiBO is provided (http://www.higis.org.cn:8080/hibo). Full article
(This article belongs to the Special Issue GIS Software and Engineering for Big Data)
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