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Special Issue "Artificial Intelligence Solutions for Geospatial Analysis: An Integrated Approach"
A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).
Deadline for manuscript submissions: closed (31 July 2019).
Prof. Dr. Jason K. Levy Website E-Mail
Disaster Preparedness and Emergency Management, University of Hawaii, Kapolei, HI 96707, USA
Interests: disaster risk governance; sustainable hazard mitigation; stochastic and statistical hydrology; sociohydrology; fluvial and marine disasters; global climate change, computational intelligence for water management; hydrologic resilience; process-based modeling of coupled human–water systems; inundation; economics of water resources management; drought
With this Special Issue on "Artificial Intelligence (AI) for Geospatial Data Analysis" we aim at taking an integrated approach to AI solutions that includes not only algorithms for intelligent geospatial data analysis, but also environmental and social dimensions, thereby fostering a robust collaboration between the Computer Science, Remote Sensing, GIScience, Social Science, and Machine Learning communities.
The intelligent collection, analysis and management Big GeoData calls for highly integrated, comprehensive and systematic approaches that relies on the expertise of scholars familiar with new AI approaches together with ethics, values and environmental issues. Artificial Intelligence (AI) techniques, algorithms and approaches are transforming society. The best AI solutions for geospatial analysis are those that include both "hard" approaches (i.e., traditional rule-based and systems) and "soft" approaches technologies (including fuzzy–neural networks) rather than relying exclusively on "connectionist" or "symbolic" paradigms. This is critically important as AI techniques, particularly machine learning, are revolutionizing the broad field of geospatial analysis. As of 2018, there were approximately three quintillion bytes of data created each day, and the pace of data creation, storage and management is increasing.
Topics include, but are not limited to:
* Integrated approaches to computer vision, speech recognition and natural language processing Object reconstruction, recognition, and classification at large scale * Application to all levels of automated systems (from semi-autonomous to fully autonomous systems
* Social science considerations off supervised, weakly supervised, transfer, and human-in-the-loop learning * Big GeoData creation, analysis and management * Applications to civilian applications, militaries, disaster management, autonomous driving, vegetation and landscape mapping.
Prospective authors are cordially invited to contribute to this Special Issue by submitting an original article that deals with one of the sub-fields until 31 January 2019. All submitting authors are strongly encouraged to test their method on a relevant benchmark data set, to compare against baseline approaches and to publicly release source code and potentially the data used in the paper, on acceptance.
Prof. Dr. Jason K. Levy
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.
- Geospatial Artificial Intelligence (AI)
- Machine Learning (e.g. Random Forests, Support Vector Machines) and Deep Learning (i.e., Neural Networks)
- Connectionism(s) vs. Symbolic Reasoning (i.e., Good Old Fashioned AI (GOFAI))
- Dynamical AI systems
- Planning, resource allocation, and decision-making