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Calibrated ratio approach for vegetation detection in shaded areas

H. Kao,H. Ren,Chao‐Shing Lee

Published 2014 in Journal of Applied Remote Sensing

ABSTRACT

Abstract Removing shadow effects remains a challenge in processing optical remote sensing data. Shadows occur because of obstructions from the terrain topography or cloud cover, which can cause errors for image classification. Shadow effects can be removed using a band-ratio approach because the shaded areas in optical images have a nearly proportional variation in the bands. We developed a calibrated band-ratio approach for shadow reduction. Before the ratio approach was applied, a regression technique was used to obtain information for calibration from the relative sensor gain and offset. After calibration, the ratio vegetation index (RVI) band ratios were calculated to process the image data, which can simultaneously remove the shadow effects and assist the search for vegetation. Real and synthesized images show that the calibrated-ratio approach can improve vegetation detection compared with standard RVI and dark pixel subtraction approaches.

PUBLICATION RECORD

  • Publication year

    2014

  • Venue

    Journal of Applied Remote Sensing

  • Publication date

    Unknown publication date

  • Fields of study

    Engineering, Environmental Science

  • Identifiers
    DOI 10.1117/1.JRS.8.083543
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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