Lessons from applying SRGAN on Sentinel-2 images for LULC classification

• Main Authors: Goh, Yun Si, Chua, Wen Qing, Yean, Seanglidet, Lee, Bu-Sung
• Other Authors: College of Computing and Data Science
• Format: Conference or Workshop Item
• Language: English
• Published: 2024
• Subjects: Computer and Information Science; Classification; Deep learning
• Online Access: https://hdl.handle.net/10356/177692
• Institution: Nanyang Technological University

Satellite images are commonly used to monitor land use land cover (LULC) changes. Unfortunately, publicly available images often lack the resolution required for detailed urban studies. In this study, we enhanced the resolution of Sentinel-2 (S2) satellite images from 10 meters to 2.5 meters using t...