Multitemporal Remote Sensing

1. Front Matter

   Pages i-xii

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2. Multitemporal Remote Sensing: Current Status, Trends and Challenges

   • Yifang Ban

   Pages 1-18

3. Change Detection Techniques: A Review

   • Yifang Ban, Osama Yousif

   Pages 19-43

4. Change Detection in Urban Areas: Spatial and Temporal Scales

   • Paolo Gamba, Fabio Dell’Acqua

   Pages 45-61

5. Change Detection in Multitemporal Hyperspectral Images

   • Lorenzo Bruzzone, Sicong Liu, Francesca Bovolo, Peijun Du

   Pages 63-88

6. Object-Based Change Detection in Urban Areas Using Multitemporal High Resolution SAR Images with Unsupervised Thresholding Algorithms

   • Osama Yousif, Yifang Ban

   Pages 89-105

7. Fusion of Multitemporal Spaceborne SAR and Optical Data for Urban Mapping and Urbanization Monitoring

   • Yifang Ban, Alexander Jacob

   Pages 107-123

8. Post-classification Change Detection in Arctic Glaciers by Multi-polarization SAR

   • Vahid Akbari, Anthony P. Doulgeris, Torbjørn Eltoft

   Pages 125-144

9. Interferometric SAR Multitemporal Processing: Techniques and Applications

   • Daniele Perissin

   Pages 145-176

10. TIMESAT for Processing Time-Series Data from Satellite Sensors for Land Surface Monitoring

    • Lars Eklundh, Per Jönsson

    Pages 177-194

11. PhenoSat – A Tool for Remote Sensing Based Analysis of Vegetation Dynamics

    • Arlete Rodrigues, André R. S. Marcal, Mário Cunha

    Pages 195-215

12. Temporal Techniques in Remote Sensing of Global Vegetation

    • Aleixandre Verger, Sivasathivel Kandasamy, Frédéric Baret

    Pages 217-232

13. Soil Moisture Dynamics Estimated from MODIS Time Series Images

    • Thomas Gumbricht

    Pages 233-253

14. Temporal Analysis of Remotely Sensed Land Surface Shortwave Albedo

    • Tao He, Shunlin Liang

    Pages 255-275

15. Observing the Response of Terrestrial Vegetation to Climate Variability Across a Range of Time Scales by Time Series Analysis of Land Surface Temperature

    • Massimo Menenti, H. R. Ghafarian Malamiri, Haolu Shang, Silvia M. Alfieri, Carmine Maffei, Li Jia

    Pages 277-315

16. A Review of Multitemporal Synthetic Aperture Radar (SAR) for Crop Monitoring

    • Heather McNairn, Jiali Shang

    Pages 317-340

17. An Approach for Determining Relationships Between Disturbance and Habitat Selection Using Bi-weekly Synthetic Images and Telemetry Data

    • Nicholas D. A. Brown, Trisalyn Nelson, Michael A. Wulder, Nicholas C. Coops, Thomas Hilker, Christopher W. Bater et al.

    Pages 341-356

18. Multitemporal Remote Sensing for Inland Water Bodies and Wetland Monitoring

    • Yeqiao Wang, Shuhua Qi, Jian Xu

    Pages 357-371

19. Global Land Surface Water Mapping and Analysis at 30 m Spatial Resolution for Years 2000 and 2010

    • Xin Cao, Jun Chen, Anping Liao, Lijun Chen, Jin Chen

    Pages 373-389

20. Multitemporal Remote Sensing of Coastal Waters

    • Susanne Kratzer, Krista Alikas, Therese Harvey, José María Beltrán-Abaunza, Evgeny Morozov, Sélima Ben Mustapha et al.

    Pages 391-426

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 varietyof 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 planetat local, regional, and global scales.

• Multitemporal Remote Sensing
• Change Detection
• Time Series Analysis
• Earth Observation Satellites
• Environmental Change Monitoring
• remote sensing/photogrammetry

• Division of Geoinformatics, KTH Royal Institute of Technology, Stockholm, Sweden

  Yifang Ban

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