Machine Learning for Geospatial Data Analysis

Dear Colleagues,

With this Special Issue on "Machine Learning for Geospatial Data Analysis" we aim at fostering collaboration between the Remote Sensing, GIScience, Computer Vision, and Machine Learning communities.

The interpretation of Big GeoData calls for highly automated approaches relying on new machine learning and data mining approaches. Extraction of meaningful information at large scale from heterogeneous, georeferenced data is a major research topic in quantitative geography, remote sensing, GIScience, cartography, geospatial computer vision, and machine learning. We invite original works to this Special Issue that apply machine learning to such diverse data, ranging from georeferenced imagery and point clouds, georeferenced text corpora and text sources, GIS databases, large-scale (online) maps or any combination of these. Data can either be acquired with dedicated (imaging) campaigns or be collected from crowd-sourced, publicly available data sets like openstreetmap or Mapillary. A major aspect is the joint processing of such data for information extraction. Topics include, but are not limited to:

• Object reconstruction, recognition, and classification at large scale
• Supervised, weakly supervised, transfer, and human-in-the-loop learning
• Joint GIS and image interpretation
• Big GeoData mining
• Applications to cities, autonomous driving, rapid hazard response, vegetation and landscape mapping.

Prospective authors are cordially invited to contribute to this theme issue by submitting an original article that deals with one of the sub-fields until 31 January 2018. 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.

Dr. Jan Dirk Wegner
Prof. Ribana Roscher
Dr. Michele Volpi
Dr. Fabio Veronesi
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 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-anonymized 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.