AI-Driven Mapping Using Remote Sensing Data
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: 15 September 2024 | Viewed by 139
Special Issue Editors
Interests: photogrammetry and remote sensing technology; intelligent spatial information processing and application; point cloud processing and application
Special Issues, Collections and Topics in MDPI journals
Interests: GeoAI; crowdsourced mapping; cognitive mapping for unmanned system; spatial data mining; location-based service
Special Issues, Collections and Topics in MDPI journals
Interests: volunteered geographic information; point cloud processing; cartographic generalization
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Mapping with remote sensing data collected from spaceborne, airborne, and terrestrial platforms has enriched the understanding of the dynamic environment and facilitated decision-making in geospatial domains. With the fast development of AI techniques such as deep learning, knowledge graphs, and large language models (or foundation models), mapping with remote sensing data has reached unprecedented levels of resolution, accuracy, semantic richness, and automation. The transfer continuum of AI advancements to the full pipeline of remote sensing data processing has become a revolutionary endeavor in modern remote sensing research. To facilitate such a research paradigm, it is worthwhile to continuously shed light on the novel applications of AI-driven mapping using remote sensing data, as well as stimulate reflective investigations of the model design principles and benchmarking basis.
This Special Issue will study the AI-driven mapping of remote sensing data by considering novel applications, model design principles, and benchmarking model performances. This Special Issue may cover topics related to AI-driven research into task-oriented remote sensing data processing and applications, data-oriented model design, and benchmark dataset construction and assessment. Articles may address, but are not limited to, the following topics:
- AI-driven interpretation of remote sensing images;
- AI-driven dynamic monitoring of land cover and land use using remote sensing data;
- AI-driven data fusion of remote sensing data and volunteered geographic information;
- AI-driven geographic registration of remote sensing data;
- AI-driven urban modeling using remote sensing and geospatial data;
- AI-driven environment sensing using mobile sensing data;
- Spatially explicit AI-driven method using remote sensing and geospatial data;
- Crowdsourcing labels for AI-driven methods using remote sensing and geospatial data.
Dr. Li Fang
Dr. Jian Yang
Dr. Yu Feng
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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
- AI-driven remote sensing
- image interpretation
- change detection
- urban modeling
- spatially explicit AI
- crowdsourced label
