Analysis Of Multi Temporal Remote Sensing Images
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Analysis of Multi Temporal Remote Sensing Images
Author | : Paul Smits,Lorenzo Bruzzone |
Publsiher | : World Scientific |
Total Pages | : 404 |
Release | : 2004-08-10 |
Genre | : Technology & Engineering |
ISBN | : 9789814482349 |
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The development of effective methodologies for the analysis of multi-temporal data is one of the most important and challenging issues that the remote sensing community will face in the coming years. Its importance and timeliness are directly related to the ever-increasing quantity of multi-temporal data provided by the numerous remote sensing satellites that orbit our planet. The synergistic use of multi-temporal remote sensing data and advanced analysis methodologies results in the possibility of solving complex problems related to the monitoring of the Earth's surface and atmosphere at different scales. However, the advances in the methodologies for the analysis of multi-temporal data have been significantly under-illuminated with respect to other remote sensing data analysis topics. In addition, the link between the end-users' needs and the scientific community needs to be strengthened. This volume of proceedings contains 43 contributions from researchers representing academia, industry and governmental organizations. It is organized into three thematic sections: Image Analysis and Algorithms; Analysis of Synthetic Aperture Radar Data; Monitoring and Management of Resources. Contents:Image Analysis and Algorithms:Extending Time-Series of Satellite Images by Radiometric Intercalibration (A Röder et al.)Trajectory of Dynamic Clusters in Image Time Series (P Heas et al.)Change Detection with ALI and Landsat Satellite Data (H Chen et al.)Analysis of Synthetic Aperture Radar Data:Multi-Temporal Interferometric Point Target Analysis (U Wegmüller et al.)Application of Multiple Baseline InSAR Data for DEM Generation (S Takeuchi)Joint Distributions for Multi-Temporal Series of Radar Images (B Storvik et al.)Monitoring and Management of Resources:Detection of Vegetation Changes in an Alpine Protected Area (M Maggi et al.)Monitoring Drought Stress in North-Eastern China by Means of Rainfall Data and Diachrone Indices Derived from Pathfinder AVHRR-Imagery (P Ozer et al.)Science for Society: Global Observations of Earth's Natural Resources in the 21st Century (R L King)and other papers Readership: Graduate students and researchers in computer science and environmental science. Keywords:Remote Sensing;Change Detection;Multi-Temporal Image Analysis;Pattern Recognition;Time Series Analysis;Environmental Monitoring;Environmental Management;Natural Resources;Earth Observation
Analysis of Multi temporal Remote Sensing Images MultiTemp 2003
Author | : Paul Smits,Lorenzo Bruzzone |
Publsiher | : Unknown |
Total Pages | : 387 |
Release | : 2004 |
Genre | : Electronic Book |
ISBN | : 9812389156 |
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Proceedings of the Second International Workshop on the Analysis of Multi Temporal Remote Sensing Images
Author | : Lorenzo Bruzzone,Paul Smits |
Publsiher | : World Scientific |
Total Pages | : 403 |
Release | : 2004 |
Genre | : Computers |
ISBN | : 9789812702630 |
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The development of effective methodologies for the analysis of multi-temporal data is one of the most important and challenging issues that the remote sensing community will face in the coming years. Its importance and timeliness are directly related to the ever-increasing quantity of multi-temporal data provided by the numerous remote sensing satellites that orbit our planet. The synergistic use of multi-temporal remote sensing data and advanced analysis methodologies results in the possibility of solving complex problems related to the monitoring of the Earth''s surface and atmosphere at different scales. However, the advances in the methodologies for the analysis of multi-temporal data have been significantly under-illuminated with respect to other remote sensing data analysis topics. In addition, the link between the end-users'' needs and the scientific community needs to be strengthened.This volume of proceedings contains 43 contributions from researchers representing academia, industry and governmental organizations. It is organized into three thematic sections: Image Analysis and Algorithms; Analysis of Synthetic Aperture Radar Data; Monitoring and Management of Resources.
Proceedings of the First International Workshop on the Analysis of Multi temporal Remote Sensing Images
Author | : Lorenzo Bruzzone |
Publsiher | : World Scientific |
Total Pages | : 455 |
Release | : 2002 |
Genre | : Technology & Engineering |
ISBN | : 9789810249557 |
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The development of effective methodologies for the analysis of multi-temporal data is one of the most important and challenging issues that the remote sensing community will face in the next few years. The importance and timeliness of this issue are directly related to the ever-increasing quantity of multi-temporal data provided by the numerous remote sensing satellites that orbit our planet. The synergistic use of multi-temporal remote sensing data and advanced analysis methodologies results in the possibility of solving complex problems related to the monitoring of the Earth's surface and atmosphere. This book brings together the methodological aspects of multi-temporal remote sensing image analysis, real applications and end-user requirements, presenting the state of the art in this field and contributing to the definition of common research priorities. Researchers and graduate students in the fields of environmental monitoring, remote sensing image analysis and pattern recognition will appreciate the interdisciplinary approach thanks to the articles written by experts from different scientific communities.
2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images Multi Temp 2015
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 135 |
Release | : 2015 |
Genre | : Electronic Book |
ISBN | : 146737119X |
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Multitemporal Remote Sensing
Author | : Yifang Ban |
Publsiher | : Springer |
Total Pages | : 448 |
Release | : 2016-12-01 |
Genre | : Technology & Engineering |
ISBN | : 9783319470375 |
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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.
2011 6th International Workshop on the Analysis of Multi temporal Remote Sensing Images
Author | : IEEE Electrical Insulation Society Staff,ieee |
Publsiher | : Unknown |
Total Pages | : 135 |
Release | : 2011-08 |
Genre | : Electronic Book |
ISBN | : 1457712024 |
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2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images Multi Temp
Author | : IEEE Staff |
Publsiher | : Unknown |
Total Pages | : 135 |
Release | : 2015-07-22 |
Genre | : Electronic Book |
ISBN | : 1467371203 |
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Promote discussion of scientific, methodological and application issues related to multitemporal data analysis Push novel solutions for technical problems related to multitemporal data, promote their use in an increasing number of applications