mlsanityData to 7 Oct 2026

The Segment Anything Model (SAM) for Remote Sensing Applications: From Zero to One Shot

arXiv 2306.16623 ↗First posted 29 Jun 2023cs.CVcited by 83

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Abstract (arXiv)

Segmentation is an essential step for remote sensing image processing. This study aims to advance the application of the Segment Anything Model (SAM), an innovative image segmentation model by Meta AI, in the field of remote sensing image analysis. SAM is known for its exceptional generalization capabilities and zero-shot learning, making it a promising approach to processing aerial and orbital images from diverse geographical contexts. Our exploration involved testing SAM across multi-scale datasets using various input prompts, such as bounding boxes, individual points, and text descriptors. To enhance the model's performance, we implemented a novel automated technique that combines a text-prompt-derived general example with one-shot training. This adjustment resulted in an improvement in accuracy, underscoring SAM's potential for deployment in remote sensing imagery and reducing the need for manual annotation. Despite the limitations encountered with lower spatial resolution images, SAM exhibits promising adaptability to remote sensing data analysis. We recommend future research to enhance the model's proficiency through integration with supplementary fine-tuning techniques and other networks. Furthermore, we provide the open-source code of our modifications on online repositories, encouraging further and broader adaptations of SAM to the remote sensing domain.

Key facts. Cited by 83 papers in the map (data through 7 Oct 2026). Builds on 34 of its 77 references that are in the map. First posted on arXiv 29 Jun 2023.

Builds on

34 of 77 references.

References · 34

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023Segment Anythingcited by 8,158
  3. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
  4. 2022Flamingo: a Visual Language Model for Few-Shot Learningcited by 4,337
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  11. 2020Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlationcited by 420
  12. 2023Augmented Language Models: a Surveycited by 398
22 more
  1. 2023RemoteCLIP: A Vision Language Foundation Model for Remote Sensingcited by 357
  2. 2022GLIPv2: Unifying Localization and Vision-Language Understandingcited by 275
  3. 2021LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentationcited by 259
  4. 2023Personalize Segment Anything Model with One Shotcited by 250
  5. 2022UniFormer: Unifying Convolution and Self-attention for Visual Recognitioncited by 206
  6. 2021Object Detection in Aerial Images: A Large-Scale Benchmark and Challengescited by 202
  7. 2020RSVQA: Visual Question Answering for Remote Sensing Datacited by 197
  8. 2020FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understandingcited by 181
  9. 2023Transformer-Based Visual Segmentation: A Surveycited by 124
  10. 2018Land-Cover Classification with High-Resolution Remote Sensing Images Using Transferable Deep Modelscited by 118
  11. 2023On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligencecited by 88
  12. 2020Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagerycited by 73
  13. 2022Transformers in Remote Sensing: A Surveycited by 61
  14. 2019Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Imagescited by 32
  15. 2021A Review on Deep Learning in UAV Remote Sensingcited by 32
  16. 2021Semantic Segmentation of Remote Sensing Images with Sparse Annotationscited by 30
  17. 2020Few-shot Object Detection on Remote Sensing Imagescited by 23
  18. 2022AI Security for Geoscience and Remote Sensing: Challenges and Future Trendscited by 23
  19. 2021Panoptic Segmentation Meets Remote Sensingcited by 14
  20. 2021Semantic Segmentation with Labeling Uncertainty and Class Imbalancecited by 12
  21. 2020A CNN Approach to Simultaneously Count Plants and Detect Plantation-Rows from UAV Imagerycited by 11
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 11; 2024: 30; 2025: 27; 2026: 15.

83 papers.

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  1. 2023Adapting Segment Anything Model for Change Detection in HR Remote Sensing Imagescited by 56
  2. 2023SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraintscited by 35
  3. 2024EarthMarker: A Visual Prompting Multi-modal Large Language Model for Remote Sensingcited by 29
  4. 2024PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Imagescited by 24
  5. 2024On Efficient Variants of Segment Anything Model: A Surveycited by 16
  6. 2025ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Objectcited by 15
  7. 2024OAM-TCD: A globally diverse dataset of high-resolution tree cover mapscited by 14
  8. 2023When Geoscience Meets Foundation Models: Towards General Geoscience Artificial Intelligence Systemcited by 13
  9. 2024Change Detection Between Optical Remote Sensing Imagery and Map Data via Segment Anything Model (SAM)cited by 12
  10. 2024Towards Satellite Image Road Graph Extraction: A Global-Scale Dataset and A Novel Methodcited by 10
  11. 2024ASANet: Asymmetric Semantic Aligning Network for RGB and SAR image land cover classificationcited by 10
  12. 2025No time to train! Training-Free Reference-Based Instance Segmentationcited by 9
38 more
  1. 2024A Multispectral Automated Transfer Technique (MATT) for machine-driven image labeling utilizing the Segment Anything Model (SAM)cited by 8
  2. 2024Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labelscited by 8
  3. 2024Prompt-Based Segmentation at Multiple Resolutions and Lighting Conditions using Segment Anything Model 2cited by 8
  4. 2025UrbanSAM: Learning Invariance-Inspired Adapters for Segment Anything Models in Urban Constructioncited by 8
  5. 2023GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentationcited by 7
  6. 2025Bringing SAM to new heights: Leveraging elevation data for tree crown segmentation from drone imagerycited by 6
  7. 2023SAM-OCTA: Prompting Segment-Anything for OCTA Image Segmentationcited by 5
  8. 2024Zero-Shot Automatic Annotation and Instance Segmentation using LLM-Generated Datasets: Eliminating Field Imaging and Manual Annotation for Deep Learning Model Developmentcited by 5
  9. 2025Delineate Anything: Resolution-Agnostic Field Boundary Delineation on Satellite Imagerycited by 5
  10. 2025OccuFly: A 3D Vision Benchmark for Semantic Scene Completion from the Aerial Perspectivecited by 5
  11. 2023Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaulcited by 4
  12. 2024FMARS: Annotating Remote Sensing Images for Disaster Management using Foundation Modelscited by 4
  13. 2024ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything Modelcited by 4
  14. 2024EchoONE: Segmenting Multiple echocardiography Planes in One Modelcited by 4
  15. 2025Rethinking Few-Shot Medical Image Segmentation by SAM2: A Training-Free Framework with Augmentative Prompting and Dynamic Matchingcited by 4
  16. 2025Assessing SAM for Tree Crown Instance Segmentation from Drone Imagerycited by 4
  17. 2026Farmland Extent and Visible Boundary Mapping from 1 m NAIP Imagery Using Residual U-Net and Text-Prompted SAM 3 Refinementcited by 4
  18. 2023GEM: Boost Simple Network for Glass Surface Segmentation via Vision Foundation Modelscited by 3
  19. 2023OBSUM: An object-based spatial unmixing model for spatiotemporal fusion of remote sensing imagescited by 3
  20. 2024MoPEFT: A Mixture-of-PEFTs for the Segment Anything Modelcited by 3
  21. 2024Investigating the Segment Anything Foundation Model for Mapping Smallholder Agriculture Field Boundaries Without Training Labelscited by 3
  22. 2024Earth System Data Cubes: Avenues for advancing Earth system researchcited by 3
  23. 2025On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentationcited by 3
  24. 2026Boosting Segment Anything Model to Generalize Visually Non-Salient Scenarioscited by 3
  25. 2026From crown candidates to neighborhood screening: integrating optical GeoAI and spatial modeling for urban-canopy assessment in Davis, Californiacited by 3
  26. 2023Prompt-Driven Building Footprint Extraction in Aerial Images with Offset-Building Modelcited by 2
  27. 2024SA-MixNet: Structure-aware Mixup and Invariance Learning for Scribble-supervised Road Extraction in Remote Sensing Imagescited by 2
  28. 2024TransLandSeg: A Transfer Learning Approach for Landslide Semantic Segmentation Based on Vision Foundation Modelcited by 2
  29. 2024Tuning a SAM-Based Model with Multi-Cognitive Visual Adapter to Remote Sensing Instance Segmentationcited by 2
  30. 2025UCS: A Universal Model for Curvilinear Structure Segmentationcited by 2
  31. 2025Post-Hurricane Debris Segmentation Using Fine-Tuned Foundational Vision Modelscited by 2
  32. 2025SRMF: A Data Augmentation and Multimodal Fusion Approach for Long-Tail UHR Satellite Image Segmentationcited by 2
  33. 2026LLM Agent Framework for Intelligent Change Analysis in Urban Environment using Remote Sensing Imagerycited by 2
  34. 2023Zero-Shot Refinement of Buildings' Segmentation Models using SAMcited by 1
  35. 2024FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anythingcited by 1
  36. 2024Leveraging Segment Anything Model in Identifying Buildings within Refugee Camps (SAM4Refugee) from Satellite Imagery for Humanitarian Operationscited by 1
  37. 2024VideoSAM: A Large Vision Foundation Model for High-Speed Video Segmentationcited by 1
  38. 2024Slender Object Scene Segmentation in Remote Sensing Image Based on Learnable Morphological Skeleton with Segment Anything Modelcited by 1

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