Special Issue "Upscaling AI Solutions for Large Scale Mapping Applications"

Dear Colleagues,

Artificial Intelligence (AI) is entering all domains, with innovative solutions and results that would have been both unpredictable and unachievable just a few years ago. In a few words, AI (including machine and deep learning methods) is the ability of computers to perform a task that typically requires some level of human intelligence. AI is bringing advantages in many fields, and everybody is talking about the adoption of AI methods to solve problems and process data.

Geospatial AI, i.e., the use of AI for the processing and understanding of large geospatial data, is also growing. Geospatial data include images and point clouds captured and generated from spaceborne and airborne sensors or mobile mapping platforms. Recently, interesting research results have been presented for point cloud classification, object detection, feature extraction, semantic segmentation, etc. Nonetheless, the challenge remains on how to apply these methods and results to nationwide 3D data sets and how to have solutions that are reliable, replicable, and applicable to National Mapping and Cadastral Agencies (NMCA) problems.

This IJGI Special Issue is organized in collaboration with EuroSDR (http://eurosdr.net/)—European Spatial Data Research, a not-for-profit organization linking NMCAs with research institutes and universities in Europe for the purpose of applied research in spatial data provision, management, and delivery.

The Special Issue aims to raise awareness and understanding of AI methods applied to large geodata as well as to collect ongoing research activities, best practices, method evaluations, and applications to boost the use of AI within the context of NMCA. The Special Issue also aims to understand the impact, benefits, effect, and open issues of AI applied to large geospatial datasets. 

Topics

Authors are invited to submit papers related to:

• Geo-information derived with Artificial Intelligence methods
• Machine and deep learning applied to large geodata
• Large-scale point cloud classification
• AI-based objected detection in large satellite or aerial image blocks
• Geodata processing boosted by AI
• Extraction of 2D and 3D geo-information from large geospatial datasets
• Benchmarks related to GeoAI
• Validation of AI methods on very large geospatial data
• Geospatial analytics for NMCA applications
• AI Cloud computing applied to large geodata
• Requirements of AI methods for NMCA needs and other relevant governmental organizations
• GeoAI applications

Prof. Dr. Fabio Remondino
Prof. Dr. ir. Joep Crompvoets
Prof. Norbert Haala
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 1400 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.

• Artificial Intelligence
• NMCA
• geospatial
• mapping
• benchmark
• large scale
• geo-information