Special Issue "Machine Learning for Multi-Source Remote Sensing Images Analysis"
Deadline for manuscript submissions: closed (16 June 2023) | Viewed by 7774
Interests: artificial intelligence; machine learning; data mining; data fusion; precision agriculture; biosystems; engineering; automation; sensors; yield prediction; crop disease detection; weed management
Special Issues, Collections and Topics in MDPI journals
Special Issue in Remote Sensing: Remote Sensing and AI Algorithms for Plant Disease and Tree Health Detection
Special Issue in Agriculture: Applications of Data Analysis in Agriculture
Special Issue in Remote Sensing: Crop Disease Detection Using Remote Sensing Image Analysis II
The recent emergence of learning methods comprises a powerful driving force of artificial intelligence technology that has greatly stimulated the enthusiasm of various research fields to utilize machine learning to solve existing problems. Several outstanding machine learning models have been widely used, achieving good performances in multi-object and multiscale remote sensing image segmentation, classification, clustering, object recognition, anomaly detection and prediction. The information from images from multiple sources can be combined to achieve improved accuracy and more specific inferences compared to those that could be achieved by the use of a single source alone. Therefore, machine learning algorithms are considered as a synergistic framework instead of solely a collection of tools and methods for integration. This could be attributed to the complex data processing steps involved in the related machine learning processes.
Remote sensing images and data provide critical information about how solar energy is partitioned into different compartments in natural systems. The application of machine learning methods to remote sensing images and data with different spatial, spectral, radiometric, and temporal resolutions can be used for pre-processing, retrieval, analysis, interpretation, and mapping in an iterative and holistic way, supporting various types of decision analysis for sustainable development.
The current special issue aims to share quality research concerning the application of machine learning techniques to remote sensing images acquired from several sources for increasing the data usability and quality of remote sensing images. Latest advances and trends of restoration and reconstruction algorithms and applications for remote sensing image processing will be presented, addressing novel approaches and practical solutions for multimodal remote sensing data processing and analysis applications.
Topics of interest include but are not limited to the following:
- Remote sensing image fusion;
- Remote sensing image super-resolution;
- Deep learning for multimodal land use and land cover classification/mapping;
- Advanced ANNs for large-scale and even global object classification and recognition;
- Multi-modal data fusion, analysis, and interpretation;
- Multi-temporal remote sensing data for time series analysis;
- Neural architectures optimized for multimodal remote sensing;
- Feature fusion and learning for anomaly and object detection.
Dr. Xanthoula Eirini Pantazi
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.
- artificial neural networks
- imaging spectroscopy analysis
- deep learning
- pattern recognition and data mining
- data regression and classification
- multi-spectral image and data processing
- data fusion
- image fusion
- information fusion
- sensor fusion