Advances in Deep Learning and Machine Learning for Remote Sensing Image Analysis
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 20 January 2026 | Viewed by 926
Special Issue Editors
Interests: remote sensing; UAV imaging; plant phenomics; precision agriculture; crops mapping; artificial intelligence; big-data analytics
Special Issues, Collections and Topics in MDPI journals
Interests: image analysis; multimodal image fusion; computer vision; deep learning; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: geomatics; remote sensing; earth observation; optical and synthetic aperture radar; artificial intelligence; machine learning; agro-environmental applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The field of remote sensing has witnessed a remarkable surge in both the quality and quantity of the data generated, with significant advancements in its spatiotemporal resolution. Concurrently, machine learning and image processing methodologies have experienced substantial progress, particularly in big data analytics. These two advancements have broadened the scope of remote sensing applications across a range of fields such as environmental sciences, agriculture, geosciences, and civil engineering. Machine learning, deep learning, and generative AI techniques have created powerful tools such as non-linear relationship mapping, vision language models, object recognition, image segmentation, and sophisticated detection algorithms, which hold immense potential for enhancing remote sensing applications. When integrated with traditional remote sensing methods, these advanced machine learning approaches could pave the way for innovative solutions in multi-source data fusion, computer vision, and predictive analytics. This integration is crucial for advancing the analysis of remote sensing images, making it an exciting and rapidly evolving area of research.
The scale and complexity of machine learning approaches and the availability of multi-source remote sensing data are significant challenges in handling big data and developing high-performance computational strategies for remote sensing applications. Addressing these challenges requires advancements in machine learning, deep learning techniques capable of managing large datasets, and methods for multi-source data fusion to enhance object detection, image segmentation, classification, and other remote sensing tasks. We invite submissions on themes including imagery data analysis, remote sensing, machine learning, deep learning, computer vision, big data, high-performance computing (HPC), predictive analytics, multi-source/sensor data fusion, object detection and recognition, and image segmentation. This Special Issue highlights cutting-edge research and innovative solutions in these areas, contributing to the advancement of remote sensing image analysis, which is in alignment with the scope of Remote Sensing.
We encourage submissions of both regular research papers and reviews on topics, including, but not limited to, the following:
- Machine and deep learning models in remote sensing;
- Image processing and computer vision;
- RGB, multispectral, and hyperspectral imaging;
- Thermal and LiDAR imagery data;
- Advanced remote sensing applications;
- Large language models for remote sensing;
- The application of generative AI in remote sensing imagery;
- Big data and predictive analytics.
Dr. Keshav D. Singh
Dr. Abdul Bais
Dr. Saeid Homayouni
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
- imagery data analysis
- remote sensing
- machine learning
- deep learning
- computer vision
- exploiting big data
- HPC and predictive analytics
- multi-source/sensor data fusion
- object detection and recognition
- image segmentation
- large language models
- generative AI
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