Urbanization and Land Use Analysis using Satellite Imagery

• Course: Image Mining (M2 IA, Paris-Saclay)
• Team: Thibault Poux, Simon Khan, Feddy Immoula
• Status: In Progress

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📌 Project Overview

This project aims to analyze urban expansion and land use changes using Sentinel-1/2 (SAR/optical) and Landsat satellite data. We focus on detecting and classifying newly artificialized areas (e.g., buildings, roads, parking lots) and comparing the performance of SAR vs. optical imagery for land use monitoring.

Key Objectives:

• Detect artificialization using SAR image comparison.
• Compare results with optical imagery at the same locations (precision, computational cost).
• Classify new artificialized areas (e.g., buildings, roads, parking lots).

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🛠️ Methodology

1. Data Sources

• Sentinel-1 (SAR): For change detection in urban areas.
• Sentinel-2 & Landsat (Optical): For land cover classification and validation.
• Dataset: Sentinel-1/2 Image Pairs – Fusing Multi-modal Data for Supervised Change Detection

available here (until 12/12/2025):