Earth Observation Monitoring and Mapping Using Multi- and Hyperspectral Satellites
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Earth Observation Data".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 122
Special Issue Editors
Interests: earth observation; geoinformatics; geospatial AI; multi-sensor data; natural hazards; open-source geospatial science
Special Issues, Collections and Topics in MDPI journals
Interests: earth observation; geospatial AI; geoinformatics; 3D visualisation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Earth observation using satellite-based multi- and hyperspectral data has become an essential approach for monitoring and mapping the Earth’s surface and its dynamic processes. With the continuous development of satellite sensors, such as Sentinel, Landsat, PRISMA, EnMAP and other hyperspectral missions, large volumes of spectral data with improved spatial, temporal and spectral resolution are now available. These data provide valuable information for understanding land cover, vegetation condition, water quality, geological features, urban environments and climate-related changes. However, challenges remain in data processing, information extraction, sensor integration and application-oriented analysis, which require further methodological and practical research.
The aim of this Special Issue is to present recent advances in Earth observation monitoring and mapping utilising multi- and hyperspectral satellite data. The Special Issue is closely aligned with the scope of the journal, as it focuses on remote sensing theory, data analysis methods and real-world applications. It seeks to bring together researchers and practitioners working on sensor development, data fusion, algorithm design and applied case studies, in order to promote the effective use of spectral satellite data for environmental and Earth system studies.
Suggested themes for submissions include, but are not limited to: multi- and hyperspectral image processing and analysis; feature extraction and classification methods; data fusion of multi-source remote sensing data; vegetation, agriculture, forestry and ecosystem monitoring; water and coastal environment applications; geological and soil mapping; urban and land-use analysis; the use of machine learning and artificial intelligence for spectral data interpretation. Both original research articles and comprehensive review papers are welcome, as well as methodological studies and application-driven case studies demonstrating the practical value of multi- and hyperspectral satellite observations.
Dr. Vasil Yordanov
Dr. Gordana Jakovljević
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-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
- earth observation
- multi-spectral remote sensing
- hyperspectral satellite data
- environmental monitoring
- land cover and land use mapping
- data fusion image processing and analysis machine learning applications
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