Journal of Marine Sciences ›› 2014, Vol. 32 ›› Issue (4): 27-34.DOI: 10.3969/j.issn.1001-909X.2014.04.004

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Reeds and suaeda biomass estimation model based on HJ-1 hyperspectal image in the Yellow River Estuary

REN Guang-bo 1, ZHANG Jie 1, WANG Wei-qi 2, GENG Yan-jie 2, CHEN Yan-jun 2, MA Yi 1   

  1. 1. First Institute of Oceanography, SOA, Qingdao 266063,China;
    2. College of Information Science and Engineering, Ocean University of China, Qingdao 266063, China
  • Received:2014-05-14 Revised:2014-09-04 Online:2014-12-15 Published:2022-11-25

Abstract: Wetland vegetation biomass is the basic information of wetland ecological assessment, protection and utilization. Remote sensing has become one of the most efficient technologies of wetland biomass monitoring. Utilizing the HJ-1 hyperspectral remote sensing image that acquired in September 2013 and the coinstantaneous field survey data, the biomass estimation capabilities of 7 kinds of narrow-band vegetation indices and 2 kinds of red edge position indices of reeds and suaeda in the Yellow River Estuary have been studied. The results reveal that (1) In single variable estimation model case, for reeds, the SRI index with 635 nm and 827 nm bands and REP_ linear interpolation index get the best R2 measures, and for suaeda, the NDVI and SRI indices with 692 nm and 807 nm bands and OSAVI index get the best biomass estimation results. (2) In multiple variable case, for reeds and suaeda, the R2 measure get 0.71 and 0.66 respectively.

Key words: biomass remote sensing, HJ-1 hyperspectral image, vegetation indices, red edge position indices

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