Multitemporal Remote Sensing

Methods and Applications

  • Yifang Ban

Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 20)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Yifang Ban, Osama Yousif
    Pages 19-43
  3. Paolo Gamba, Fabio Dell’Acqua
    Pages 45-61
  4. Lorenzo Bruzzone, Sicong Liu, Francesca Bovolo, Peijun Du
    Pages 63-88
  5. Vahid Akbari, Anthony P. Doulgeris, Torbjørn Eltoft
    Pages 125-144
  6. Arlete Rodrigues, André R. S. Marcal, Mário Cunha
    Pages 195-215
  7. Aleixandre Verger, Sivasathivel Kandasamy, Frédéric Baret
    Pages 217-232
  8. Massimo Menenti, H. R. Ghafarian Malamiri, Haolu Shang, Silvia M. Alfieri, Carmine Maffei, Li Jia
    Pages 277-315
  9. Nicholas D. A. Brown, Trisalyn Nelson, Michael A. Wulder, Nicholas C. Coops, Thomas Hilker, Christopher W. Bater et al.
    Pages 341-356
  10. Xin Cao, Jun Chen, Anping Liao, Lijun Chen, Jin Chen
    Pages 373-389
  11. Susanne Kratzer, Krista Alikas, Therese Harvey, José María Beltrán-Abaunza, Evgeny Morozov, Sélima Ben Mustapha et al.
    Pages 391-426
  12. Tuong-Thuy Vu, Daroonwan Kamthonkiat
    Pages 427-445

About this book


Written by world renowned scientists, this book provides an excellent overview of a wide array of methods and techniques for the processing and analysis of multitemporal remotely sensed images. These methods and techniques include change detection, multitemporal data fusion, coarse-resolution time series processing, and interferometric SAR multitemporal processing, among others. A broad range of multitemporal datasets are used in their methodology demonstrations and application examples, including multispectral, hyperspectral, SAR and passive microwave data.  

This book features a variety of application examples covering both land and aquatic environments. Land applications include urban, agriculture, habitat disturbance, vegetation dynamics, soil moisture, land surface albedo, land surface temperature, glacier and disaster recovery. Aquatic applications include monitoring water quality, water surface areas and water fluctuation in wetland areas, spatial distribution patterns and temporal fluctuation trends of global land surface water, as well as evaluation of water quality in several coastal and marine environments.

This book will help scientists, practitioners, students gain a greater understanding of how multitemporal remote sensing could be effectively used to monitor our changing planet at local, regional, and global scales.


Multitemporal Remote Sensing Change Detection Time Series Analysis Earth Observation Satellites Environmental Change Monitoring

Editors and affiliations

  • Yifang Ban
    • 1
  1. 1.Division of GeoinformaticsKTH Royal Institute of TechnologyStockholmSweden

Bibliographic information

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