Examining the utility of hyperspectral remote sensing and partial least squares to predict plant stress responses to sulphur dioxide pollution: a case study of Trichilia dregeana Sond.

摘要: AbstractThe use of air quality monitoring stations is expensive, with pollution data being either unavailable or inaccessible. Hence, effects atmospheric sulphur dioxide (SO2) levels on biomarkers related to environmental stress were investigated for Trichilia dregeana tree leaves, in order assess their bioindicator potential. Leaves sampled randomly from trees at three industrial sites within the South Durban Basin, and an ex situ control, across two seasons (n = 28, per season). Ground-level SO2 concentrations measured daily ranged between 1 25 ppb. There significant (p < 0.001) differences leaf area chlorophyll content. Partial least squares regression (PLSR) was used quantify relationship hyperspectral data. For content area, r2 values 0.325–0.475 0.429–0.586, root mean square error prediction (RMSEP) ranging 8.75–8.98 9.20–12.52. The variable im...