mlsanityData to 7 Oct 2026

State Space Models Meet Remote Sensing: A Survey

arXiv 2606.25329 ↗First posted 24 Jun 2026cs.CV cs.LGcited by 0

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Abstract (arXiv)

State Space Models (SSMs), designed for long-range modeling, offer linear computational complexity and strong capabilities in capturing long-range dependencies. In the field of remote sensing, SSMs have gained popularity due to their effectiveness in addressing unique challenges such as dense visual predictions, multi-modal remote sensing data, and temporal remote sensing data, which have also yielded significant advancements in customized architectures. This paper presents a comprehensive review of SSM-based approaches in remote sensing, covering most of the relevant studies since SSMs were first introduced to the field. We offer a multi-dimensional analysis examining SSM applications in remote sensing tasks and discussing advancements in architecture design. This paper not only synthesizes the rapid progress in SSM-based research but also identifies key challenges and future opportunities. By providing a detailed perspective, this paper aims to serve as a foundational resource for remote sensing researchers, offering actionable insights to foster further advancements in this evolving domain. We will keep tracing related works at https://github.com/QinzheYang/Awesome-RS-State-Space-Model.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 125 of its 197 references that are in the map. First posted on arXiv 24 Jun 2026.

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References · 125

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38 more
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  1. 2026A Controlled Benchmark of Visual State-Space Backbones with Domain-Shift and Boundary Analysis for Remote-Sensing Segmentation
  2. 2024CHOICE: Benchmarking the Remote Sensing Capabilities of Large Vision-Language Models
  3. 2024GG-SSMs: Graph-Generating State Space Models
  4. 2025Remote Sensing-Oriented World Model
  5. 2024RS3Mamba: Visual State Space Model for Remote Sensing Images Semantic Segmentation
  6. 2024Foundation Models for Remote Sensing and Earth Observation: A Survey
  7. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagery
  8. 2025UniTS: Unified Spatio-Temporal Generative Model for Remote Sensing