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Clear-cut Detection in Boreal Forest Aided by Remote Sensing.

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Title: Clear-cut Detection in Boreal Forest Aided by Remote Sensing.
Authors: Saksa, Timo1 (AUTHOR) timo.saksa@metla.fi, Uuttera, Janne2 (AUTHOR), Kolström, Taneli3 (AUTHOR), Lehikoinen, Mikko4 (AUTHOR), Pekkarinen, Anssi5 (AUTHOR), Sarvi, Vesa6 (AUTHOR)
Source: Scandinavian Journal of Forest Research. Dec2003, Vol. 18 Issue 6, p537-546. 10p.
Subjects: Taigas, Remote-sensing images, Landsat satellites, Forests & forestry
Abstract: The study compares the applicability of different remote sensing data and digital change detection methods in detecting clear-cut areas in boreal forest. The methods selected for comparisons are simple and straightforward and thus applicable in practical forestry. The data tested were from Landsat satellite imagery and high-altitude panchromatic aerial orthophotographs. The change detection was based on image differencing. Three different approaches were tested: (1) pixel-by-pixel differencing and segmentation; (2) pixel block-level differencing and thresholding; and (3) presegmentation and unsupervised classification. The study shows that the methods and data sources used are accurate enough for operational detection of clear-cut areas. The study suggests that predelineated segments or pixel blocks should be used for image differencing to decrease the number of misinterpreted small areas. For the same reason the use of a digital forest mask is crucial in operational applications. [ABSTRACT FROM AUTHOR]
Copyright of Scandinavian Journal of Forest Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Clear-cut Detection in Boreal Forest Aided by Remote Sensing.
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  Data: <searchLink fieldCode="AR" term="%22Saksa%2C+Timo%22">Saksa, Timo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> timo.saksa@metla.fi</i><br /><searchLink fieldCode="AR" term="%22Uuttera%2C+Janne%22">Uuttera, Janne</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kolström%2C+Taneli%22">Kolström, Taneli</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lehikoinen%2C+Mikko%22">Lehikoinen, Mikko</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pekkarinen%2C+Anssi%22">Pekkarinen, Anssi</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sarvi%2C+Vesa%22">Sarvi, Vesa</searchLink><relatesTo>6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Scandinavian+Journal+of+Forest+Research%22">Scandinavian Journal of Forest Research</searchLink>. Dec2003, Vol. 18 Issue 6, p537-546. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Taigas%22">Taigas</searchLink><br /><searchLink fieldCode="DE" term="%22Remote-sensing+images%22">Remote-sensing images</searchLink><br /><searchLink fieldCode="DE" term="%22Landsat+satellites%22">Landsat satellites</searchLink><br /><searchLink fieldCode="DE" term="%22Forests+%26+forestry%22">Forests & forestry</searchLink>
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  Label: Abstract
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  Data: The study compares the applicability of different remote sensing data and digital change detection methods in detecting clear-cut areas in boreal forest. The methods selected for comparisons are simple and straightforward and thus applicable in practical forestry. The data tested were from Landsat satellite imagery and high-altitude panchromatic aerial orthophotographs. The change detection was based on image differencing. Three different approaches were tested: (1) pixel-by-pixel differencing and segmentation; (2) pixel block-level differencing and thresholding; and (3) presegmentation and unsupervised classification. The study shows that the methods and data sources used are accurate enough for operational detection of clear-cut areas. The study suggests that predelineated segments or pixel blocks should be used for image differencing to decrease the number of misinterpreted small areas. For the same reason the use of a digital forest mask is crucial in operational applications. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Scandinavian Journal of Forest Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/02827580310016881
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      – Code: eng
        Text: English
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        PageCount: 10
        StartPage: 537
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      – SubjectFull: Taigas
        Type: general
      – SubjectFull: Remote-sensing images
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      – SubjectFull: Landsat satellites
        Type: general
      – SubjectFull: Forests & forestry
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      – TitleFull: Clear-cut Detection in Boreal Forest Aided by Remote Sensing.
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            NameFull: Saksa, Timo
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            NameFull: Uuttera, Janne
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            NameFull: Kolström, Taneli
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            NameFull: Lehikoinen, Mikko
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            NameFull: Pekkarinen, Anssi
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            NameFull: Sarvi, Vesa
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            – D: 01
              M: 12
              Text: Dec2003
              Type: published
              Y: 2003
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              Value: 18
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            – TitleFull: Scandinavian Journal of Forest Research
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