articleIEEE Geoscience and Remote Sensing MagazineMar 7, 2025Closed access

Vision Foundation Models in Remote Sensing: A survey

Vanderbilt University · Oak Ridge National Laboratory · +1 more institution

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Abstract

Artificial intelligence (AI) technologies have profoundly transformed the field of remote sensing (RS), revolutionizing data collection, processing, and analysis. Traditionally reliant on manual interpretation and task-specific models, RS research has been significantly enhanced by the advent of foundation models (FMs)—large-scale pretrained AI models capable of performing a wide array of tasks with unprecedented accuracy and efficiency. This article provides a comprehensive survey of FMs in the RS domain. We categorize these models based on their architectures, pretraining datasets, and methodologies. Through detailed performance comparisons, we highlight emerging trends and the significant advancements…

Citation impact

61
total citations
FWCI
63.03
Percentile
100%
References
96
Citations per year

Authors

8

Topics & keywords

Keywords
  • Foundation (evidence)
  • Remote sensing
  • Computer science
  • Meteorology
  • Geology
  • Geography
  • Archaeology
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