Change Detection and Image Time Series Analysis 2

Supervised Methods

Abdourrahmane M. Atto, Francesca Bovolo, Lorenzo Bruzzone (University of Trento, Italy)

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English

ISTE Ltd
07 December 2021

Digital photography: consumer & user guides; Computer vision; Image processing

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.

Edited by: Abdourrahmane M. Atto, Francesca Bovolo, Lorenzo Bruzzone (University of Trento, Italy)
Imprint: ISTE Ltd
Country of Publication: United Kingdom
Edition: 2nd Edition
Dimensions: Height: 10mm, Width: 10mm,
Weight: 454g
ISBN: 9781789450576
ISBN 10: 1789450578
Pages: 272
Publication Date: 07 December 2021
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Abdourrahmane M. Atto is Associate Professor at the University Savoie Mont Blanc, France. His research interests include mathematical methods and models for artificial intelligence and image time series. Francesca Bovolo is the Head of the Remote Sensing for Digital Earth Unit, Fondazione Bruno Kessler, Italy. Her research interests include remote sensing image time series analysis, content-based time series retrieval and radar sounders. Lorenzo Bruzzone is Professor of Telecommunications and the Founder and Director of the Remote Sensing Laboratory at the University of Trento, Italy. His research interests include remote sensing, machine learning and pattern recognition.