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Multitemporal Remote Sensing

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Cover of 'Multitemporal Remote Sensing'

Table of Contents

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    Book Overview
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    Chapter 1 Multitemporal Remote Sensing: Current Status, Trends and Challenges
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    Chapter 2 Change Detection Techniques: A Review
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    Chapter 3 Change Detection in Urban Areas: Spatial and Temporal Scales
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    Chapter 4 Change Detection in Multitemporal Hyperspectral Images
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    Chapter 5 Object-Based Change Detection in Urban Areas Using Multitemporal High Resolution SAR Images with Unsupervised Thresholding Algorithms
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    Chapter 6 Fusion of Multitemporal Spaceborne SAR and Optical Data for Urban Mapping and Urbanization Monitoring
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    Chapter 7 Post-classification Change Detection in Arctic Glaciers by Multi-polarization SAR
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    Chapter 8 Interferometric SAR Multitemporal Processing: Techniques and Applications
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    Chapter 9 TIMESAT for Processing Time-Series Data from Satellite Sensors for Land Surface Monitoring
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    Chapter 10 PhenoSat – A Tool for Remote Sensing Based Analysis of Vegetation Dynamics
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    Chapter 11 Temporal Techniques in Remote Sensing of Global Vegetation
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    Chapter 12 Soil Moisture Dynamics Estimated from MODIS Time Series Images
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    Chapter 13 Temporal Analysis of Remotely Sensed Land Surface Shortwave Albedo
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    Chapter 14 Observing the Response of Terrestrial Vegetation to Climate Variability Across a Range of Time Scales by Time Series Analysis of Land Surface Temperature
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    Chapter 15 A Review of Multitemporal Synthetic Aperture Radar (SAR) for Crop Monitoring
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    Chapter 16 An Approach for Determining Relationships Between Disturbance and Habitat Selection Using Bi-weekly Synthetic Images and Telemetry Data
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    Chapter 17 Multitemporal Remote Sensing for Inland Water Bodies and Wetland Monitoring
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    Chapter 18 Global Land Surface Water Mapping and Analysis at 30 m Spatial Resolution for Years 2000 and 2010
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    Chapter 19 Multitemporal Remote Sensing of Coastal Waters
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    Chapter 20 Monitoring Long-Term Disaster Recovery – Space and Ground Views
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Title
Multitemporal Remote Sensing
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-47037-5
ISBNs
978-3-31-947035-1, 978-3-31-947037-5
Editors

Yifang Ban

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X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 23%
Student > Ph. D. Student 12 15%
Student > Bachelor 8 10%
Researcher 8 10%
Student > Doctoral Student 7 9%
Other 15 18%
Unknown 13 16%
Readers by discipline Count As %
Environmental Science 25 30%
Earth and Planetary Sciences 16 20%
Engineering 12 15%
Agricultural and Biological Sciences 7 9%
Chemistry 3 4%
Other 4 5%
Unknown 15 18%