Abstract
Dryland salinity is a major land management issue globally, and results in the abandonment of farmland. Revegetation with halophytic shrub species such as Atriplex nummularia for carbon mitigation may be a viable option but to generate carbon credits ongoing monitoring and verification is required. This study investigated the utility of high-resolution airborne images (Digital Multi Spectral Imagery (DMSI)) obtained in two seasons to estimate carbon stocks at the plant- and stand-scale. Pixel-scale vegetation indices, sub-pixel fractional green vegetation cover for individual plants, and estimates of the fractional coverage of the grazing plants within entire plots, were extracted from the high-resolution images. Carbon stocks were correlated with both canopy coverage (R2: 0.76–0.89) and spectral-based vegetation indices (R2: 0.77–0.89) with or without the use of the near-infrared spectral band. Indices derived from the dry season image showed a stronger correlation with field measurements of carbon than those derived from the green season image. These results show that in semi-arid environments it is better to estimate saltbush biomass with remote sensing data in the dry season to exclude the effect of pasture, even without the refinement provided by a vegetation classification. The approach of using canopy cover to refine estimates of carbon yield has broader application in shrublands and woodlands.
Highlights
Global climate change is resulting from an imbalance in global greenhouse gas emissions [1].A major strategy to mitigate carbon dioxide emissions is to sequester or remove carbon from the atmosphere through changing land use and increasing storage in plant biomass or soils [2,3]
normalized difference vegetation index (NDVI), ratio vegetation index (RVI), SAVI, green chromatic coordinate (GCC), and fc all showed significant differences (p < 0.001) between pasture and saltbush, which are expected given the different absorption features of the red and NIR spectral bands used in these vegetation indices
This study suggests that there is a potential to use high spatial resolution airborne digital multispectral imagery to rapidly estimate the carbon storage of shrublands resulting from revegetation of abandoned farmland
Summary
Global climate change is resulting from an imbalance in global greenhouse gas emissions [1]. A major strategy to mitigate carbon dioxide emissions is to sequester or remove carbon from the atmosphere through changing land use and increasing storage in plant biomass or soils [2,3]. 83% of the mitigation targets or Intended Nationally Determined Contributions (INDCs) published following the 2015 Paris Climate Change Conference included the land sector [4]. Carbon mitigation activities on farmland can displace food production [5] or affect water supplies [6]. Alternative mitigation approaches have been advocated, such as using low value or otherwise abandoned farmland to avoid competitive effects of vegetation [7]. In 2002, about 20,000 farms and 2 million hectares of agricultural land showed actual signs of salinity [8], and up to 170,000 km of land in Australia is predicted to be affected from salinity by
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