Field Boundary Detection in Satellite Imagery Using the SAM2 Model | by Mahyar Aboutalebi, Ph.D. 🎓 | Nov, 2024


Step-by-Step Tutorial on Applying Segment Anything Model Version 2 to Satellite Imagery for Detecting and Exporting Field Boundaries in Agricultural Areas

Towards Data Science
  1. 🌟 Introduction
  2. 🏷️ Segment Anything Model
  3. 🚀 Setup Google Colab
  4. 🛰️ Load Clear Sentinel-2 Images
  5. 🌍 Apply SAM2 on Sentinel-2 Images
  6. 📄 Conclusion
  7. 📚 References

🌟 Introduction

Manually drawing field boundaries is one of the most time-consuming tasks, and its accuracy depends on the performance of the person doing it. However, accurate boundary detection has applications in many areas. For example, let’s assume you want to train a machine learning algorithm to analyze the relationship between vegetation indices from satellite images and crop yields on a farm. The first input you’ll need is a shapefile of the farm, which typically has to be drawn manually. Drawing one shapefile may only take a few minutes, but what if you need to draw boundaries for 1,000 farms? That’s when the process becomes very time consuming…

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