Mires and Peat (Aug 2020)

Identifying spectral features of characteristics of Sphagnum to assess the remote sensing potential of peatlands: A case study in China

  • Y. Pang,
  • Y. Huang,
  • Y. Zhou,
  • J. Xu,
  • Y. Wu

DOI
https://doi.org/10.19189/MaP.2019.OMB.StA.1834
Journal volume & issue
Vol. 26, no. 25
pp. 1 – 19

Abstract

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Sphagnum mosses are the dominant species of natural peatlands, which are important in the global carbon cycle. There is increasing interest in the use of sensors mounted on satellites or unmanned aerial vehicles in association with management of the ecological resources of peatlands, e.g. for monitoring purposes. Since Sphagnum mosses grow with many other vascular plants in the same habitat, the spectral signals of Sphagnum moss pixels in the remote sensing image are mixed, so investigation of their spectral characteristics forms a basis for remote sensing of peatlands. In this study, the spectral characteristics of Sphagnum magellanicum Brid were analysed at various levels (field and laboratory hyperspectral, laboratory plant physiology, satellite sensors) and compared with those of other plants, in order to examine the potential for developing remote sensing methods to distinguish Sphagnum. The results showed that: (1) the unique spectral characteristics of S. magellanicum that might be used to distinguish it from other plants are located in the near-infrared and shortwave infrared (NIR-SWIR; 760–2400 nm) region of the reflectance spectrum, and especially in the two water absorption bands (980 and 1150 nm); (2) the cell structure of S. magellanicum (which is the basis of its large water-holding capacity) explains the very low reflectance in the NIR-SWIR and the sensitivity of reflectance in the IR to moisture; and (3) the identification of Sphagnum from satellite remote sensing data should be based on sensors which have more infrared channels such as Sentinel-2A MSI, and on vegetation indices established in the NIR-SWIR such as MSI (moisture stress index) and NDII (normalised difference infrared index).

Keywords