Remote sensing data analysis and interpretation present unique challenges due to the diversity in sensor modalities and spatiotemporal dynamics of Earth observation data. Mixture-of-Experts (MoE) model has emerged as a powerful paradigm that addresses these challenges by dynamically routing inputs to specialized experts designed for different aspects of a task. However, despite rapid progress, the community still lacks a comprehensive review of MoE for remote sensing. This survey provides the first systematic overview of MoE applications in remote sensing, covering fundamental principles, architectural designs, and key applications across a variety of remote sensing tasks. The survey also outlines future trends to inspire further research and innovation in applying MoE to remote sensing.
@article{arxiv.2604.03342,
title = {Mixture-of-Experts in Remote Sensing: A Survey},
author = {Yongchuan Cui and Peng Liu and Lajiao Chen},
journal= {arXiv preprint arXiv:2604.03342},
year = {2026}
}