Geospatial Intelligence in Remote Sensing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing for Geospatial Science".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 1081
Special Issue Editors
Interests: natural disaster/emergency management; geospatial epidemiology; data science; artificial intelligence; machine learning; satellite image classification
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Advancements in remote sensing and geospatial intelligence are reshaping the understanding of spatial data. Many researchers have been using machine learning algorithms and sophisticated statistical approaches in remote sensing. In the last few years, innovations in artificial intelligence (AI) in the geospatial field, known as GeoAI or geospatial AI, have significantly enhanced our ability to process and interpret spatial data. Visual interpretation of 2D and 3D remote sensing data plays a vital role in structure failure assessment and monitoring, land use and land cover mapping, geomorphology, and disaster and climate change research, among others. Leveraging these advancements in geospatial intelligence in remote sensing has fostered scientific solutions for tackling challenges in structural monitoring, environmental monitoring, disaster risk reduction and management, urban planning, and climate change adaptation.
This issue aims to compile groundbreaking research that underlines the nexus between geospatial intelligence and remote sensing, aligning with the journal’s focus on advancing our understanding of remote sensing technologies and their applications. This is a platform for researchers to highlight how GeoAI approaches can enhance remote sensing data interpretation and address real-world issues. Therefore, the main objective is to contribute to the journal’s mission of promoting impactful advancements in remote sensing among the scientific community as well as policy practitioners.
We invite scientists, researchers, and practitioners to submit their original articles, reviews, and case studies. Themes revolve around the latest breakthroughs and applications of geospatial intelligence in remote sensing, which include but, are not limited to, the following:
- Machine learning applications in remote sensing;
- 3D point cloud processing;
- Disaster management and climate change adaptation;
- Environmental monitoring and management;
- Infrastructure;
- Urban planning and development;
- Mining;
- Agriculture and food security.
Dr. Samsung Lim
Dr. Badal Pokharel
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
- geospatial intelligence
- remote sensing
- machine learning
- spatial analysis
- GeoAI
- 3D point cloud processing
- environmental monitoring
- satellite image classification
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