Deep Learning For Remote Sensing And Geodata

This article discusses the use of Artificial Intelligence (AI) in remote sensing data analysis, specifically in land-use observation, change detection, and water quality monitoring. The lack of labeled data and benchmark datasets for training AI models is identified as a major obstacle in global-scale deployment. The evolution of AI from classical machine learning models to deep learning and foundational models is also explored, with a focus on the comparison and generalizability of these models for various applications. The article encourages submissions of original manuscripts that focus on scalable AI methodologies and benchmark dataset creation for remote sensing data analysis.