Abstract
4th edition of IEEE Geoscience and Remote Sensing Society (GRSS) ESI HDCRS School.
IEEE GRSS and Activities of HDCRS Working Group
The IEEE Geoscience and Remote Sensing Society (GRSS) focuses on advancing the science and technology of remote sensing and disseminating knowledge in this field. The society supports various technical committees and working groups that promote research, development, and education in geoscience and remote sensing. One such group is the “High-performance and Disruptive Computing in Remote Sensing” (HDCRS) of the GRSS Earth Science Informatics Technical Committee (ESI TC). HDCRS is the main organizer of this school, and its primary objective is to connect a community of interdisciplinary researchers in remote sensing who specialize in distributed computing (such as supercomputing and cloud computing), disruptive computing (e.g., quantum computing), and parallel programming models with specialized hardware (e.g., GPUs, FPGAs). The activities of HDCRS include educational events, special sessions, and tutorials at conferences, as well as publication activities, which will be presented
Advancing Geoscience through Large-Scale AI with Supercomputing for Earth Observation and Remote Sensing
The rapid proliferation of data has increased the complexity of data-driven problems across various scientific and engineering fields. This shift has spurred advancements in AI, particularly in unsupervised and self-supervised learning, and multimodal learning. Significant progress is evident not only in mainstream Natural Language Processing and Computer Vision but also in Earth observation applications. These advancements leverage the synergy between self-supervised learning and the expanded availability of High-Performance Computing (HPC) systems, leading to the rise of AI Foundation Models (FMs). These models, developed by training on large and diverse datasets, capture a broad spectrum of informative features, making them versatile across multiple domains.
