Mixture-of-Experts in Remote Sensing: A Survey

• URL: http://arxiv.org/abs/2604.03342v1
• Date: Fri, 03 Apr 2026 09:43:43 GMT
• Title: Mixture-of-Experts in Remote Sensing: A Survey
• Abstract summary: This survey provides the first overview of MoE applications in remote sensing.<n>It covers fundamental principles, architectural designs and key applications across a variety of remote sensing tasks.<n>It also outlines future trends to inspire further research and innovation in applying MoE to remote sensing.
• Score: 3.2165374538840594
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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