Meet the editor

Prof. Dr. Maged Marghany is the author of "Advanced Remote Sensing Technology for Tsunami Modelling and Forecasting" which was published by Routledge Taylor and Francis Group, CRC. Prof. Dr. Maged Marghany is currently a professor of microwave remote sensing at Geomatika University College, Malaysia. He has led several projects related to the application of SAR to Malaysian coastal waters, funded by the Ministry of Sci-

ence and Technology, Malaysia (MOSTE) and also the Ministry of High Education in Malaysia (MOHE). His research is directed towards the use of synthetic aperture radar (SAR) data for modeling shoreline changes and developing a new approach for forecasting oil slick trajectory movements. He teaches at postgraduate levels on the topic of digital image processing and microwave remote sensing.

Prof. Maged Marghany established a new research method regarding four-dimensional forecasting, which was published in his book "Advanced Remote Sensing Technology for Tsunami Modelling and Forecasting" in addition to involving quantum theory for forecasting tsunamis.

Prof. Dr. Maged Marghany (1967) was awarded the ESA Post-doctoral Fellowship by the International Institute of Aerospace and Earth Observation (ITC) in Enschede, the Netherlands, funded by the European Space Agency (ESA) for one year from March 2000 to March 2001. Prof. Dr. Maged has published over 270 papers in international conferences and indexed journals. He is also the editor of three books published by the rapidly growing IntechOpen publisher.

**Preface III**

Synthetic Aperture Radar Image Processing and Applications **1**

**Chapter 1 3**

**Chapter 2 15** On Feature-Based SAR Image Registration: Appropriate Feature and Retrieval

**Chapter 3 47** L-Band SAR Disaster Monitoring for Harbor Facilities Using Interferometric

Advanced Image Data Processing **65**

**Chapter 4 67** Utilization of Deep Convolutional Neural Networks for Remote Sensing Scenes

**Chapter 5 85** Sub-Pixel Technique for Time Series Analysis of Shoreline Changes Based on

Reconstruction **105**

**Chapter 6 107**

Infrastructure Investigations, Tsunami Disaster Mapping and Novel 3-D

Utilization of Dynamic and Static Sensors for Monitoring Infrastructures

*by Chang Luo, Hanqiao Huang, Yong Wang and Shiqiang Wang*

Introductory Chapter: Advanced Ocean Current Simulation from TanDEM

**Section 1**

Contents

Satellite Data *by Maged Marghany*

Algorithm

Analysis *by Ryo Natsuaki*

**Section 2**

Classification

**Section 3**

Multispectral Satellite Imagery *by Qingxiang Liu and John C. Trinder*

*by Chung C. Fu, Yifan Zhu and Kuang-Yuan Hou*

*by Dong Li, Yunhua Zhang and Xiaojin Shi*

## Contents



Preface

The advance in space machineries has created a novel technology for observing and monitoring the Earth from space. Most earth observation remote sensing considerations focus on using conventional image processing algorithms or classic edge detection tools. Nevertheless, these techniques do not implement modern physics, applied mathematics, signal communication, remote sensing data, and innovative space technologies. This book provides readers with methods to comprehend how to monitor coastal environments, disaster areas, and infrastructure from space with advanced talent remote sensing technology to bridge the gaps between modern space technology, image processing algorithms, mathematical models and the critical issue of the coastal and infrastructure investigations. In other words, advanced remote sensing technology, which covers sensor developments, and image processing algorithm modifications, which are based on modern physics, artificial intelligence, and machine learning. In these regards, their applications cover a wide range of coastal observations, for instances, high risk of a tsunami depends on the depth of water, the coastal geomorphology, the direction of the tsunami wave, and the existence of rivers or other water canals. In these circumstances, coastal zones are required for new urban planning and specific infrastructure designing to reduce

In spite of numerous of synthetic aperture radar (SAR) space technology, the developing country researchers and scientists are still focusing on optical remote sensing technology. In fact, microwave remote sensing require use of mathematics and physics behind the SAR technology. The first chapter introduces a new technology for measuring sea surface current using along-track interferometry of TanDEM-X satellite data. This chapter delivers a novel algorithm to retrieve sea surface current using the multichannel MAP height estimator algorithm, which is considered the first study of ocean current in the coastal waters of Peninsular

The available SAR data increases dramatically with the recent operation of many spaceborne and airborne SAR systems. This makes the joint processing of multiple images for accurate understanding and perception of a scene and target possible. For SAR image pairs acquired from different imaging geometries or by different sensors, there is always a geometrical warp between them, which should be compensated first before any deep application. Image registration is aimed to retrieve the warp function to align the same pixel position in each SAR image to the same target position in the global system. A lot of SAR image registration techniques have been developed hitherto. In the second chapter, the algorithms that conduct registration based on image features, such as contour, region, line, and point are accurately addressed. Contour, region, and line, as well as their combinations, are often used for registration of multi-modality images. For SAR images with geometrical distortion and speckle, point feature is generally much clearer and easier extracted. Tie points, corner, and key points are the commonly-used features in SAR image registration. Tie points usually refer to the features extracted from tie

the impact of such a disaster.

patches in SAR image registration.

Malaysia.
