Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.2
3.4
Journals
IJGI
Special Issues
Spatial Data Infrastructure for Distributed Management and Processing
share announcement

Spatial Data Infrastructure for Distributed Management and Processing

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 11313

Special Issue Editors

Prof. Dr. Alberto Belussi

E-Mail Website
Guest Editor
Department of Computer Science, University of Verona, 37129 Verona, Italy
Interests: spatial big data systems; spatio-temporal data analysis; spatial query processing; conceptual design of spatial databases; spatial constraints; spatial data validation
Special Issues, Collections and Topics in MDPI journals
Dr. Sara Migliorini

E-Mail Website
Guest Editor
Department of Computer Science, University of Verona, 37134 Verona, Italy
Interests: data management; spatiotemporal information systems; big data and analytics; collaborative and distributed architectures; blockchain technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the amount of available spatial data has grown considerably: technological advances in acquisition methods and tools have made it possible to collect an unprecedented amount of high-resolution and high-quality spatial data, while the proliferation of Internet-based technologies has allowed different organizations to share these data for paying off acquisition and maintenance costs.

A set of organizations interested in maintaining and processing a certain portion of spatial data can build a virtual organization. The coordination of these new entities is possible thanks to the development of a common spatial data infrastructure (SDI) that is becoming a reality in many countries. A spatial data infrastructure is a technological infrastructure through which several organizations with overlapping goals can share data, resources, tools, and competencies in an effective way. Large SDIs require new, effective techniques to continuously integrate spatial data coming from different sources and characterized by different quality levels.

This Special Issue aims at promoting new and innovative studies, proposing new architectures or innovative evolutions of existing ones, and illustrating experiments on current technologies in order to support the construction and maintenance of an integrated spatial data infrastructures.

We invite submissions of either original technical papers or high-quality survey papers that shed new light on a particular perspective on distributed systems for big spatial data.

Prof. Dr. Alberto Belussi
Prof. Dr. Sara Migliorini
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 submissions that pass pre-check are 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 1700 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

  • Spatial data infrastructure (SDI)
  • Big spatial (or spatio-temporal) data management
  • Multiresolution spatial data integration
  • Interoperability within SDI
  • Integration of geo-crowdsourced datasets with SDI
  • Distributed spatial data processing
  • SmartCity analytics.

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

28 pages, 6956 KiB  
Article
A Subject-Sensitive Perceptual Hash Based on MUM-Net for the Integrity Authentication of High Resolution Remote Sensing Images
by Kaimeng Ding, Yueming Liu, Qin Xu and Fuqiang Lu
ISPRS Int. J. Geo-Inf. 2020, 9(8), 485; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9080485 - 11 Aug 2020
Cited by 10 | Viewed by 2381
Abstract
Data security technology is of great significance to the application of high resolution remote sensing image (HRRS) images. As an important data security technology, perceptual hash overcomes the shortcomings of cryptographic hashing that is not robust and can achieve integrity authentication of HRRS [...] Read more.
Data security technology is of great significance to the application of high resolution remote sensing image (HRRS) images. As an important data security technology, perceptual hash overcomes the shortcomings of cryptographic hashing that is not robust and can achieve integrity authentication of HRRS images based on perceptual content. However, the existing perceptual hash does not take into account whether the user focuses on certain types of information of the HRRS image. In this paper, we introduce the concept of subject-sensitive perceptual hash, which can be seen as a special case of conventional perceptual hash, for the integrity authentication of HRRS image. To achieve subject-sensitive perceptual hash, we propose a new deep convolutional neural network architecture, named MUM-Net, for extracting robust features of HRRS images. MUM-Net is the core of perceptual hash algorithm, and it uses focal loss as the loss function to overcome the imbalance between the positive and negative samples in the training samples. The robust features extracted by MUM-Net are further compressed and encoded to obtain the perceptual hash sequence of HRRS image. Experiments show that our algorithm has higher tamper sensitivity to subject-related malicious tampering, and the robustness is improved by about 10% compared to the existing U-net-based algorithm; compared to other deep learning-based algorithms, this algorithm achieves a better balance between robustness and tampering sensitivity, and has better overall performance. Full article
(This article belongs to the Special Issue Spatial Data Infrastructure for Distributed Management and Processing)
►▼ Show Figures

Figure 1

20 pages, 7150 KiB  
Article
A Decentralized Model for Spatial Data Digital Rights Management
by Yun Zhang, Zhi Tang, Jing Huang, Yue Ding, Hao He, Xiaosheng Xia and Chunhua Li
ISPRS Int. J. Geo-Inf. 2020, 9(2), 84; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9020084 - 01 Feb 2020
Cited by 8 | Viewed by 3584
Abstract
The copyright of data is a key point that needs to be solved in spatial data infrastructure for data sharing. In this paper, we propose a decentralized digital rights management model of spatial data, which can provide a novel way of solving the [...] Read more.
The copyright of data is a key point that needs to be solved in spatial data infrastructure for data sharing. In this paper, we propose a decentralized digital rights management model of spatial data, which can provide a novel way of solving the existing copyright management problem or other problems in spatial data infrastructure for data sharing. An Ethereum smart contract is used in this model to realize spatial data digital rights management function. The InterPlanetary File System is utilized as external data storage for storing spatial data in the decentralized file system to avoid data destruction that is caused by a single point of failure. There is no central server in the model architecture, which has a completely decentralized nature and it makes spatial data rights management not dependent on third-party trust institutions. We designed three spatial data copyright management algorithms, developed a prototype system to implement and test the model, used the smart contract security verification tool to check code vulnerabilities, and, finally, discussed the usability, scalability, efficiency, performance, and security of the proposed model. The result indicates that the proposed model not only has diversified functions of copyright management compared with previous studies on the blockchain-based digital rights management, but it can also solve the existing problems in traditional spatial data infrastructure for data sharing due to its characteristics of complete decentralization, mass orientation, immediacy, and high security. Full article
(This article belongs to the Special Issue Spatial Data Infrastructure for Distributed Management and Processing)
►▼ Show Figures

Figure 1

Review

Jump to: Research

22 pages, 3274 KiB  
Review
Towards Self-Service GIS—Combining the Best of the Semantic Web and Web GIS
by Alexandra Rowland, Erwin Folmer and Wouter Beek
ISPRS Int. J. Geo-Inf. 2020, 9(12), 753; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9120753 - 15 Dec 2020
Cited by 18 | Viewed by 4483
Abstract
The field of geographic information science has grown exponentially over the last few decades and, particularly within the context of the pervasiveness of the internet, bears witness to a rapid transition of its associated technologies from stand-alone systems to increasingly networked and distributed [...] Read more.
The field of geographic information science has grown exponentially over the last few decades and, particularly within the context of the pervasiveness of the internet, bears witness to a rapid transition of its associated technologies from stand-alone systems to increasingly networked and distributed systems as geospatial information becomes increasingly available online. With its long-standing history for innovation, the field has adopted many disruptive technologies from the fields of computer and information sciences through this transition towards web geographic information systems (GIS); most interestingly in the context of this research is the limited uptake of semantic web technologies by the field and its associated technologies, the lack of which has resulted in a technological disjoint between these fields. As the field seeks to make geospatial information more accessible to more users and in more contexts through ‘self-service’ applications, the use of these technologies is imperative to support the interoperability between distributed data sources. This paper aims to provide insight into what linked data tooling already exists, and based on the features of these, what may be possible for the achievement of self-service GIS. Findings include what visualisation, interactivity, analytics and usability features could be included in the realisation of self-service GIS, pointing to the opportunities that exist in bringing GIS technologies closer to the user. Full article
(This article belongs to the Special Issue Spatial Data Infrastructure for Distributed Management and Processing)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop