4.7 Article

Using Spectral Indices to Estimate Water Content and GPP in Sphagnum Moss and Other Peatland Vegetation

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2019.2961479

关键词

Vegetation mapping; Indexes; Carbon; Hyperspectral imaging; Ecosystems; Moisture; Hyperspectral data; multispectral data; optical data; vegetation and land surface

资金

  1. James Hutton Institute
  2. Natural Environment Research Council (NERC), SCENARIO DTP [NE/L002566/1]
  3. Scottish Government through Strategic Research Programme 2016-2021
  4. Engineering and Physical Sciences Research Council Twenty-65 Project [EP/N010124/1]
  5. NERC, National Centre for Earth Observation (NCEO) [NE/R016518/1]
  6. EU LIFE
  7. Peatland Action
  8. Heritage Lottery Fund (HLF)
  9. Royal Society for the Protection of Birds (RSPB)

向作者/读者索取更多资源

Peatlands provide important ecosystem services including carbon storage and biodiversity conservation. Remote sensing shows potential for monitoring peatlands, but most off-the-shelf data products are developed for unsaturated environments and it is unclear how well they can perform in peatland ecosystems. Sphagnum moss is an important peatland genus with specific characteristics which can affect spectral reflectance, and we hypothesized that the prevalence of Sphagnum in a peatland could affect the spectral signature of the area. This article combines results from both laboratory and field experiments to assess the relationship between spectral indices and the moisture content and gross primary productivity (GPP) of peatland (blanket bog) vegetation species. The aim was to consider how well the selected indices perform under a range of conditions, and whether Sphagnum has a significant impact on the relationships tested. We found that both water indices tested [normalized difference water index (NDWI) and floating water band index (fWBI)] were sensitive to the water content changes in Sphagnum moss in the laboratory, and there was little difference between them. Most of the vegetation indices tested [the normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), structure insensitive pigment index (SIPI), and chlorophyll index (CIm)] were found to have a strong relationship with GPP both in the laboratory and in the field. The NDVI and EVI are useful for large-scale estimation of GPP, but are sensitive to the proportion of Sphagnum present. The CIm is less affected by different species proportions and might therefore be the best to use in areas where vegetation species cover is unknown. The photochemical reflectance index (PRI) is shown to be best suited to small-scale studies of single species.

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