Estimating fractional cover of plant functional types in African savannah from harmonic analysis of MODIS time-series data

Assessments of tree/grass fractional cover in savannahs using remote sensing are challenging due to the heterogeneous mixture of the two plant functional types. Time-series decomposition models can be used to characterize vegetation phenology from satellite data, but have rarely been used for attributing phenological signal components to different plant functional types. Here, tree/grass dynamics are assessed in savannah ecosystems using time-series decomposition of 14 years of Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index data acquired from 2002 to 2015. The decomposition method uses harmonic analysis and tests the individual harmonic terms for statistical significance. Field data of fractional cover of trees and grasses were collected for 28 plots in Kruger National Park, South Africa. Matching MODIS pixels were analysed for their tree/grass phenological signals. Tree/grass annual and interannual variability were then assessed based on the harmonic models. In most harmonic cycles, grass-dominated sites had higher amplitudes than tree-dominated sites, while the tree green-up started earlier than grasses, before the start of the wet season. While changes in tree phenology are gradual, grasses present higher variability over time. Tree cover showed a significant correlation with the amplitude (r (correlation coefficient) = −0.59, p = 0.001) and phase of the first harmonic term (r = −0.73, p = 0.0001) and the number of cycles of the second harmonic term (r = 0. 56, p = 0.002). Grass cover was also significantly correlated with the amplitude (r = 0. 51, p = 0.005) and phase of the first harmonic term (r = 0.55, p = 0.002) and the number of cycles of the second harmonic term (r = −0.52, p = 0.005). The positive correlation of grass cover with phase and negative correlation with number of cycles is indicating a late greening period and higher variability, respectively. Tree cover estimated from the phase of the strongest harmonic term showed a positive correlation with field-measured tree cover (R2 (coefficient of determination) = 0.55, p < 0.01, slope = 0.93, root mean square error = 13.26%). The estimated tree cover also had a strong correlation with the woody cover map (r = 0.78, p < 0.01) produced by Bucini. The results show that MODIS time-series data can be used to estimate the fractional tree cover in heterogeneous savannahs from the phase of the plant functional type’s phenological behaviour. This study shows that harmonic analysis is able to discriminate between fractional cover by trees and grasses in savannahs. The quantitative analysis of tree/grass phenology from satellite time-series data enables a better understanding of the dynamics of the tree/grass competition and coexistence

Height-specific biomass change as a function of relative height change per grid cell.

<p>Height categories are a) 1–3 m, b) 3–5 m and c) 5–10 m for rangelands of high, intermediate and low wood extraction pressure. There were no data for the 5–10 m height class in the high wood extraction rangeland and the >10 m height class for all rangelands as there were no grid cells with an average height over 10 m. Grid cell size: 25 m x 25 m.</p

Mean biomass increase (Mg ha^-1) at sites under varying wood extraction pressures.

<p>n is the number of 25 m x 25 m grid cells in each rangeland.</p><p>Mean biomass increase (Mg ha^-1) at sites under varying wood extraction pressures.</p

Height-specific biomass change as a function of relative change in canopy cover per grid cell.

<p>Height categories are a) 1–3 m, b) 3–5 m and c) 5–10 m for rangelands of high, intermediate and low wood extraction pressure. There were no data for the 5–10 m height class in the high wood extraction rangeland and the >10 m height class for all rangelands as there were no grid cells with an average height over 10 m. Grid cell size: 25 m x 25 m.</p

Study sites in Bushbuckridge municipality, located in the South African Lowveld.

<p>Sites are classified (from west to east) as low, high and intermediate wood extraction pressure based on the number of households and people utilising each rangeland. Settlements that utilise each rangeland are shown, including the names of the major settlements, as well as the location of the gabbro intrusions in the predominantly granitic landscape.</p

Site-specific biomass models derived from field allometry and LiDAR metric linear regression.

<p>In the model equations, y refers to the plot-level (25 m x 25 m) biomass estimate (kg/625 m²) and x to the LiDAR-derived H x CC predictor metrics, where H is plot-averaged height (> 1.5 m) and CC is the proportion of canopy cover (> 1.5 m in height) per plot. Root mean square error (RMSE) was reported in Mg ha^-1 for ease of interpretation and n is number of 25 m x 25 m plots.</p><p>Site-specific biomass models derived from field allometry and LiDAR metric linear regression.</p

Height-specific subcanopy returns (%) (mean ± standard deviation) for 2008 and 2012.

<p>Wood extraction levels are: a) high (n = 102 cells), b) intermediate (n = 291 cells), and c) low wood extraction (n = 1654 cells). Contribution of height class change (subcanopy returns) to total change (total vegetation column) (%) is the black bar represented by values on the secondary axis. e.g. In the high wood extraction rangeland, 79% of the change in the total vegetation column was attributable to the 1–3 m height class.</p

Height-specific correlation (p < 0.001) between change in biomass (%) and subcanopy returns (%).

<p>Wood extraction levels for each rangeland are listed per column as high, intermediate and low.</p