Characterizing the spatio-temporal variations of C3 and C4 dominated grasslands aboveground biomass in the Drakensberg, South Africa
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
C3 and C4 grass species composition, with different physiological, morphological and most importantly phenological
characteristics, influence Aboveground Biomass (AGB) and their ability to provide ecosystem goods
and services, over space and time. For decades, the lack of appropriate remote sensing data sources compromised
C3 and C4 grasses AGB estimation, over space and time. This resulted in uncertainties in understanding their
potential and contribution to the provision of services. This study therefore examined the utility of the new
multi-temporal Sentinel 2 to estimate and map C3 and C4 grasses AGB over time, using the advanced Sparse
Partial Least Squares Regression (SPLSR) model. Overall results have shown the variability in AGB between C3
and C4 grasses, estimation accuracies and the performance of the SPLSR model, over time. Themeda (C4) produced
higher AGB from February to April, whereas from May to September, Festuca produced higher AGB. Both
species also showed a decrease in AGB in August and September, although this was most apparent for Themeda
than its counterpart. Spectral bands information predicted species AGB with lowest accuracies and an improvement
was observed when both spectral bands and vegetation indices were applied. For instance, in the
month of May, spectral bands predicted species AGB with lowest accuracies for Festuca (R2=0.57; 31.70% of
the mean), Themeda (R2=0.59; 24.02% of the mean) and combined species (R2=0.61; 15.64% of the mean);
the use of spectral bands and vegetation indices yielded 0.77; (18.64%), 0.75 (14.27%) and 0.73 (16.47%), for
Festuca, Themeda and combined species, respectively. The red edge (at 0.705 and 0.74 μm) and derived indices,
NIR and SWIR 2 (2.19 μm) were found to contribute more to grass species AGB estimation, over time. Findings
have also revealed the potential of the SPLSR model in estimating C3 and C4 grasses AGB using Sentinel 2
images, over time. The AGB spatial variability maps produced in this study can be used to quantify C3 and C4
forage availability or accumulating fuel, as well as for developing operational management strategies.
Description
Keywords
Environmental changes, Forage availability, Red edge, Seasonal variations, Species functional types
Citation
Shoko, C. et al. (2018).Characterizing the spatio-temporal variations of C3 and C4 dominated grasslands aboveground biomass in the Drakensberg, South Africa. International Journal of Applied Earth Observation and Geoinformation, 68: 51 – 60