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author:

Chen, J. (Chen, J..) [1] | Xu, H. (Xu, H..) [2]

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Scopus

Abstract:

The red-edge band is closely related to biochemical parameters that characterize the growth condition of green plants and is an important factor in monitoring vegetation health. Therefore, red-edge indices based on the red-edge band have been developed to measure vegetation health. However, due to the limited availability of satellites with a red-edge band, most existing red-edge indices were not developed based on satellite data. Fortunately, the launch of the GaoFen-6 (GF-6) satellite provides favorable conditions for monitoring vegetation health using satellite imagery, as it has two red-edge bands with a spatial resolution of 16 m. To investigate the effectiveness of the red-edge bands on the GF-6 satellite in monitoring forest health, this study selected six red-edge indices and conducted tests in Zhangjiajie region in Hunan Province, China and Hetian Basin in Fujian Province, China. The selected indices are the normalized difference red-edge index 1 (NDRE1), the modified chlorophyll absorption ratio index 2, the red-edge chlorophyll (CIred-edge), the inverted red-edge chlorophyll index, the red-edge position, and the Missouri emergency resource information system terrestrial chlorophyll index. The results showed that when applied to NDRE1 and CIred-edge, the red-edge bands of GF-6 can effectively distinguish forest health conditions, with a discrimination accuracy of 92.3% and 92.5%, respectively. However, the performance of the GF-6 red-edge bands with the other four indices yielded accuracy generally lower than 70%. Overall, the two red-edge bands added to the GF-6 satellite contribute to discerning forest health conditions, with NDRE1 and CIred-edge being the preferred red-edge indices.  © 2008-2012 IEEE.

Keyword:

Forest health GaoFen-6 (GF-6) red-edge band red-edge index remote sensing.

Community:

  • [ 1 ] [Chen J.]Fuzhou University, College of Environment and Safety Engineering, Institute of Remote Sensing Information Engineering, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou, 350116, China
  • [ 2 ] [Xu H.]Fuzhou University, College of Environment and Safety Engineering, Institute of Remote Sensing Information Engineering, Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou, 350116, China

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Source :

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

ISSN: 1939-1404

Year: 2024

Volume: 17

Page: 5621-5636

4 . 7 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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