Artificial Intelligence Solutions for Geospatial Analysis: An Integrated Approach

Dear Colleagues,

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
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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 1900 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.