Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data

Abstract

Globally, subtropical forests are rich in biodiversity. However, the native biodiversity in these forests is threatened by the presence of invasive species such as Chromolaena odorata (L.) King and Robinson, which thrives in forest canopy gaps. Our study explored the utility of WorldView-2 data, an 8-band high resolution (2 m) imagery for mapping the probability of C. odorata occurrence (presence/absence) in canopy gaps of a subtropical forest patch, the Dukuduku forest, South Africa. An integrated modelling approach involving the WorldView-2 vegetation indices and ancillary environmental data was also assessed. The results showed a higher performance of the environmental data only model (deviance or D 2 = 0.52, p < 0.05, n = 77) when compared to modelling with WorldView-2 vegetation indices such as the enhanced vegetation index, simple ratio indices and red edge normalized difference vegetation index (D 2 = 0.30, p < 0.05, n = 77). The integrated model explained the highest presence/absence variance of C. odorata (D 2 = 0.71, i.e. 71 %). This model was used to derive a probability map indicating the occurrence of invasive species in forest gaps. A 2 × 2 error matrix table and the receiver operating characteristic curve derived from an independent validation dataset (n = 38) were used to assess the model accuracy. Approximately 87 % of canopy gaps containing C. odorata were correctly predicted at probability threshold of 0.3. The derived probability map of C. odorata occurrence could assist management in prioritizing target areas for eradication of the species.