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Analysis Of Multi-temporal Remote Sensing Images

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Title: Analysis Of Multi-temporal Remote Sensing Images
Description: 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 relevance 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 remote sensing, image analysis, and environmental monitoring will appreciate the interdisciplinary approach thanks to the articles written by experts from different scientific communities.
Authors: Lorenzo Bruzzone, Paul C Smits
Resource Type: eBook.
Subjects: Remote sensing--Congresses
Categories: TECHNOLOGY & ENGINEERING / Electronics / General, COMPUTERS / Optical Data Processing, TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems
Database: eBook Collection (EBSCOhost)
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  Availability: 0
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DbLabel: eBook Collection (EBSCOhost)
An: 514286
RelevancyScore: 979
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PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 978.796813964844
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  Data: 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 relevance 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 remote sensing, image analysis, and environmental monitoring will appreciate the interdisciplinary approach thanks to the articles written by experts from different scientific communities.
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  Data: <searchLink fieldCode="AR" term="%22Lorenzo+Bruzzone%22">Lorenzo Bruzzone</searchLink><br /><searchLink fieldCode="AR" term="%22Paul+C+Smits%22">Paul C Smits</searchLink>
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      – Code: 621.3678
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Remote sensing--Congresses
        Type: general
    Titles:
      – TitleFull: Analysis Of Multi-temporal Remote Sensing Images
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Lorenzo Bruzzone
      – PersonEntity:
          Name:
            NameFull: Paul C Smits
      – PersonEntity:
          Name:
            NameFull: Lorenzo Bruzzone
      – PersonEntity:
          Name:
            NameFull: Paul C Smits
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2002
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9789810249557
            – Type: isbn-electronic
              Value: 9789812777249
          Numbering:
            – Type: volume
              Value: 00002
          Titles:
            – TitleFull: Analysis Of Multi-temporal Remote Sensing Images
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