Artificial Intelligence and Machine Learning for multi-source Remote Sensing

Dear Colleagues,

Recently, artificial intelligence and machine learning have gained attention and have been used to achieve great success in both the research community and industry, especially in the field of multi-source remote sensing. Due to the recent progress in machine learning, particularly in deep learning, many techniques for image analysis and understanding have been applied to solve real problems, and deep learning has been widely used to perform other computer vision tasks, such as video classification and image super-resolution. Learning an effective feature representation from a large amount of data through artificial intelligence techniques is useful for extracting the underlying structural features of the data even when a small amount of data is available. It also results in a better representation than hand-crafted features as the features learned through artificial intelligence techniques adapt well to the tasks at hand.

Currently, massive streams of Earth Observation data are being systematically collected from different cutting-edge optical and radar sensors, on-board satellites, and aerial and terrestrial platforms. These data include both images and video sequences at different spatial, spectral, and temporal resolutions and can be used to constantly monitor the Earth's surface. In order to fully exploit these datasets and deliver crucial information for numerous engineering, environmental, safety, and security applications, novel artificial intelligence and machine learning methods are required that will enable us to efficiently dissect and interpret the data and draw conclusions that the broader public can turn into action.

The scope of this Special Issue is interdisciplinary and seeks collaborative contributions from academia and industrial experts in the areas of geoscience and remote sensing, signal processing, computer vision, machine learning, and data science.

Prof. Dr. Silvia Liberata Ullo
Prof. Dr. Parameshachari Bidare Divakarachari
Prof. Dr. Pia Addabbo
Guest Editors

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