**Preface to "Artificial Intelligence-Based Learning Approaches for Remote Sensing"**

Remote sensing is a method for understanding the ground and for facilitating human–ground communications. New developments in remote sensing have led to high-resolution monitoring of the ground on a global scale, giving a huge amount of ground observation data. Thus, AI-based deep learning approaches and its applied signal processing are required for remote sensing. These approaches can be universal or specific AI tools, including well-known neural networks, regression methods, decision trees, etc. In this book, I aimed to describe recent developments and trends regarding topics such as advanced AI-based deep learning techniques and remote sensing data processing. Sixteen papers were finally published in this book.

In this book, I focus my attention on Artificial Intelligence-Based Learning Approaches for Remote Sensing. The issue is comprised of original research articles as well as some reviews, on topics such as artificial intelligence, machine learning and deep learning. The manuscripts mainly contain remote sensing research, varying from theoretical work to in application studies. Some reviews summarize the current stage of ongoing application attempts. This book contains topics, i.e., for concrete bridge defects identification, localization based on classification, multi-source real landform data, multi-label graphs, UAV visual localization, multispectral and panchromatic image fusion, prediction of weather radar data, rotated SAR ship detection and classification, AIS data based on AI, vector-based spatial data, sparse-model-driven network, machine learning and fuzzy logic, boundary-aware network for SAR ship instance segmentation, GAN for spectral domain translation of remote sensing images, lightweight deep learning detector, moving target shadow detection network, detecting pine wilt disease using RGB-based UAV images.

This book collected papers that emphasis new Artificial Intelligence-Based Learning Approaches for Remote Sensing. Furthermore, this book expects to encourage more research in the field of AI-based approaches for remote sensing.

> **Gwanggil Jeon** *Editor*
