Polarimetric rotation domain interpretation is an innovation in radar image processing and understanding. Orientation rotation is a basic operator well known in the classic polarimetry theory, and significant advancement has been made in recent years. This book presents new and advanced concepts, theories, and methodologies in radar polarimetry and bridges the gaps between target scattering diversity, polarimetric radar data, and their practical applications. It provides a comprehensive summarization and investigation of polarimetric rotation domain features and demonstrates novel applications of polarimetric radar target detection, classification, target structure recognition, and urban damage mapping. FEATURES Focuses on basic concepts, key techniques, and various applications of the polarimetric rotation domain interpretation paradigm for the first time in book form Explains, represents, and utilizes the radar target scattering diversity effect Identifies new methods for target polarimetric scattering mechanism understanding Provides a comprehensive investigation of polarimetric roll-invariant features Includes novel application developments for imaging radar target detection, structure recognition, and damage mapping This book is written for researchers and professionals in radar polarimetry, radar imaging, microwave remote sensing, environmental studies, and other related fields. Senior undergraduate and postgraduate students, as well as teachers in the same fields, will benefit from the advancements highlighted in this book.

"Polarimetric rotation domain interpretation is an innovation in radar image processing and understanding. Orientation rotation is a basic operator well-known in the classic polarimetry theory and significant advancement has been made in recent years. This book presents new and advanced concepts, theories, and methodologies in radar polarimetry and bridges the gaps between the target scattering diversity, polarimetric radar data, and their practical applications. It provides a comprehensive summarization and investigation of polarimetric roll-invariant features for researchers, students, and engineers"--

This book presents new and advanced concepts, theories and methodologies in polarimetric synthetic aperture radar (PolSAR) target scattering mechanism modeling and interpretation, which is dedicated to bridge the gap between the acquired data and practical applications. It proposes adaptive and generalized polarimetric target decompositions, to precisely interpret the target scattering mechanisms. Further, it develops a uniform polarimetric matrix rotation theory and a polarimetric coherence pattern visualization and interpretation tool to completely explore and characterize the deep information and target signatures in the rotation domain. Finally, it demonstrates land cover classification, target detection, natural disaster damage investigation and mapping applications which use the novel scattering mechanism investigation tools. The book is a valuable resource for senior undergraduate and postgraduate students, teachers, engineers and researchers in the field of microwave remote sensing, radar polarimetry, imaging radar, and environmental studies.

This book is a printed edition of the Special Issue "Advances in SAR: Sensors, Methodologies, and Applications" that was published in Remote Sensing

Change Detection and Image Time Series Analysis 2 presents supervised machine-learning-based methods for temporal evolution analysis by using image time series associated with Earth observation data. Chapter 1 addresses the fusion of multisensor, multiresolution and multitemporal data. It proposes two supervised solutions that are based on a Markov random field: the first relies on a quad-tree and the second is specifically designed to deal with multimission, multifrequency and multiresolution time series. Chapter 2 provides an overview of pixel based methods for time series classification, from the earliest shallow learning methods to the most recent deep-learning-based approaches. Chapter 3 focuses on very high spatial resolution data time series and on the use of semantic information for modeling spatio-temporal evolution patterns. Chapter 4 centers on the challenges of dense time series analysis, including pre processing aspects and a taxonomy of existing methodologies. Finally, since the evaluation of a learning system can be subject to multiple considerations, Chapters 5 and 6 offer extensive evaluations of the methodologies and learning frameworks used to produce change maps, in the context of multiclass and/or multilabel change classification issues.

The recent launches of three fully polarimetric synthetic aperture radar (PolSAR) satellites have shown that polarimetric radar imaging can provide abundant data on the Earth’s environment, such as biomass and forest height estimation, snow cover mapping, glacier monitoring, and damage assessment. Written by two of the most recognized leaders in this field, Polarimetric Radar Imaging: From Basics to Applications presents polarimetric radar imaging and processing techniques and shows how to develop remote sensing applications using PolSAR imaging radar. The book provides a substantial and balanced introduction to the basic theory and advanced concepts of polarimetric scattering mechanisms, speckle statistics and speckle filtering, polarimetric information analysis and extraction techniques, and applications typical to radar polarimetric remote sensing. It explains the importance of wave polarization theory and the speckle phenomenon in the information retrieval problem of microwave imaging and inverse scattering. The authors demonstrate how to devise intelligent information extraction algorithms for remote sensing applications. They also describe more advanced polarimetric analysis techniques for polarimetric target decompositions, polarization orientation effects, polarimetric scattering modeling, speckle filtering, terrain and forest classification, manmade target analysis, and PolSAR interferometry. With sample PolSAR data sets and software available for download, this self-contained, hands-on book encourages you to analyze space-borne and airborne PolSAR and polarimetric interferometric SAR (Pol-InSAR) data and then develop applications using this data.

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL and Python, Third Edition introduces techniques used in the processing of remote sensing digital imagery. It emphasizes the development and implementation of statistically motivated, data-driven techniques. The author achieves this by tightly interweaving theory, algorithms, and computer codes. See What’s New in the Third Edition: Inclusion of extensive code in Python, with a cloud computing example New material on synthetic aperture radar (SAR) data analysis New illustrations in all chapters Extended theoretical development The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power. The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.