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Journal of Applied Remote Sensing • Open Access

Calibrated ratio approach for vegetation detection in shaded areas
Author(s): Hung-Ming Kao; Hsuan Ren; Chao Shing Lee

Paper 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.

Paper Details

Date Published: 27 October 2014
PDF: 19 pages
J. Appl. Rem. Sens. 8(1) 083543 doi: 10.1117/1.JRS.8.083543
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Hung-Ming Kao, National Central Univ. (Taiwan)
Hsuan Ren, National Central University (Taiwan)
Chao Shing Lee, National Taiwan Ocean Univ. (Taiwan)

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