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An object-oriented daytime land fog detection approach based on NDFI and fractal dimension using EOS/MODIS data.

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Title: An object-oriented daytime land fog detection approach based on NDFI and fractal dimension using EOS/MODIS data.
Authors: Wen, Xiongfei1 (AUTHOR) wxfei19@gmail.com, Hu, Dunmei2 (AUTHOR), Dong, Xinyi3 (AUTHOR), Yu, Fan4 (AUTHOR), Tan, Debao1 (AUTHOR), Li, Zhe1 (AUTHOR), Liang, Yitong5 (AUTHOR), Xiang, Daxiang1 (AUTHOR), Shen, Shaohong1 (AUTHOR), Hu, Chengfang1 (AUTHOR), Cao, Bo1 (AUTHOR)
Source: International Journal of Remote Sensing. Jul2014, Vol. 35 Issue 13, p4865-4880. 16p.
Subjects: Earth Observing System (Program), MODIS (Spectroradiometer), Fractal dimensions, Fog control, Air quality, Remote sensing
Abstract: A new approach for land fog detection using daytime imagery from Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data based on the normalized difference fog index (NDFI) is proposed. NDFI is used to discriminate fog from clouds based on simulating and analysing the radiation characteristics of fog and cloud with MODIS data and the Streamer radiative transfer model. In this paper, in addition to the spectral and spatial characteristics of NDFI, the textural characteristics are introduced by using a fractal dimension. The fractal dimension is calculated with a differential box-counting approach to differentiate the texture characteristics of cloud and fog, and then the spectral and texture features are combined using an NDFI weighted fractal dimension algorithm as a new feature to improve the existing daytime fog detection approach. The performance of this approach is evaluated against ground-based measurements over China in winter, and the approach is proved to be effective in detecting land fog accurately based on the three cases. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Remote Sensing 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.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 97226383
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: An object-oriented daytime land fog detection approach based on NDFI and fractal dimension using EOS/MODIS data.
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  Data: <searchLink fieldCode="AR" term="%22Wen%2C+Xiongfei%22">Wen, Xiongfei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wxfei19@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Hu%2C+Dunmei%22">Hu, Dunmei</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dong%2C+Xinyi%22">Dong, Xinyi</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yu%2C+Fan%22">Yu, Fan</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tan%2C+Debao%22">Tan, Debao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zhe%22">Li, Zhe</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liang%2C+Yitong%22">Liang, Yitong</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xiang%2C+Daxiang%22">Xiang, Daxiang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shen%2C+Shaohong%22">Shen, Shaohong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hu%2C+Chengfang%22">Hu, Chengfang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cao%2C+Bo%22">Cao, Bo</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Remote+Sensing%22">International Journal of Remote Sensing</searchLink>. Jul2014, Vol. 35 Issue 13, p4865-4880. 16p.
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  Data: A new approach for land fog detection using daytime imagery from Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data based on the normalized difference fog index (NDFI) is proposed. NDFI is used to discriminate fog from clouds based on simulating and analysing the radiation characteristics of fog and cloud with MODIS data and the Streamer radiative transfer model. In this paper, in addition to the spectral and spatial characteristics of NDFI, the textural characteristics are introduced by using a fractal dimension. The fractal dimension is calculated with a differential box-counting approach to differentiate the texture characteristics of cloud and fog, and then the spectral and texture features are combined using an NDFI weighted fractal dimension algorithm as a new feature to improve the existing daytime fog detection approach. The performance of this approach is evaluated against ground-based measurements over China in winter, and the approach is proved to be effective in detecting land fog accurately based on the three cases. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Remote Sensing 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: 10.1080/01431161.2014.930564
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      – Code: eng
        Text: English
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        PageCount: 16
        StartPage: 4865
    Subjects:
      – SubjectFull: Earth Observing System (Program)
        Type: general
      – SubjectFull: MODIS (Spectroradiometer)
        Type: general
      – SubjectFull: Fractal dimensions
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      – SubjectFull: Fog control
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      – SubjectFull: Air quality
        Type: general
      – SubjectFull: Remote sensing
        Type: general
    Titles:
      – TitleFull: An object-oriented daytime land fog detection approach based on NDFI and fractal dimension using EOS/MODIS data.
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            – D: 01
              M: 07
              Text: Jul2014
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              Y: 2014
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