Multimodal Remote Sensing and Big Data Analytics for Earth Observation
A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Earth Observation Data".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 211
Editors
Interests: earth observation; remote sensing; image processing; geospatial artificial intelligence (GeoAI); agricultural and environmental monitoring; geospatial analysis
Interests: multimodal remote sensing; machine learning for earth observation; agricultural and crop monitoring; biophysical parameter estimation; explainable artificial intelligence
Special Issue Information
Dear Colleagues,
Recent advances in Earth Observation (EO) technologies have led to an unprecedented growth in the volume, variety, and velocity of geospatial data. Satellite missions (e.g., optical, SAR, hyperspectral), Unmanned Aerial Vehicles (UAVs), and in situ sensors now provide complementary perspectives for monitoring complex Earth system processes. The emergence of multimodal remote sensing, combined with big data analytics, artificial intelligence (AI), and cloud computing, has opened new possibilities, many of which were largely theoretical until recently, for extracting meaningful and timely information to address global challenges.
This Special Issue aims to present recent advances in methods and applications that leverage multimodal EO data and big data analytics for improved Earth system monitoring and modeling. It focuses on the integration of diverse data modalities and the development of innovative analytical frameworks, including machine learning and GeoAI techniques. The topic is well aligned with the scope of remote sensing, emphasizing novel approaches in data fusion, geospatial analysis, and large-scale EO data processing to support scientific research and informed decision-making.
Topics of interest include, but are not limited to, the following: multimodal data fusion and integration; deep learning and foundation models for EO; time-series analysis and change detection with multimodal data; cloud-based and high-performance geospatial computing; applications in urban, agricultural, and environmental monitoring; integration of EO with in situ and socio-economic data; and explainable AI in remote sensing. Original research articles, review papers, and case studies are welcome.
Dr. Gizem Senel
Dr. Mehmet Furkan Celik
Dr. Mustafa Serkan Isik
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. 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
- multimodal remote sensing
- big geospatial data
- data fusion
- GeoAI
- time-series analysis
- deep learning
- foundational models in remote sensing
- cloud computing
- geospatial analytics
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
