Remote sensing of the spatio-temporal distribution of invasive water hyacinth (Eichhornia crassipes) in the Greater Letaba River System in Tzaneen, South Africa

Abstract

Water hyacinth (Eichhornia crassipes) is recognised as the most notorious invasive species the world-over. Although its threats and effects are fully documented, its distribution is not yet understood, especially in complex environments, such as river systems. This has been associated with the lack of accurate (high spatial resolution) and robust techniques, together with the reliable data sources necessary for its quantification and monitoring. The advent of new generation sensors i.e. Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) data, with unique sensor design and improved sensing characteristics is therefore perceived to provide new opportunities for mapping the distribution of invasive water hyacinth in small waterbodies. This study aimed at mapping and understanding the spatio-temporal distribution of invasive water hyacinth in the Greater Letaba river system in Tzaneen, Limpopo Province of South Africa using Landsat 8 OLI and Sentinel-2 MSI data. Specifically, the study sought to identify multispectral remote sensing variables that can optimally detect and map invasive water hyacinth. Landsat 8 OLI and Sentinel-2 MSI were tested based on the spectral bands, vegetation indices, as well as the combined spectral bands plus vegetation indices, using discriminant analysis algorithm. From the findings, Sentinel-2 MSI outperformed Landsat 8 OLI in mapping water hyacinth, with an overall classification (OA) accuracy of 77.56% and 68.44%, respectively. This observation was further confirmed by a t-test statistical analysis which showed that there were significant differences (t=6.313, p<0.04) between the performance of the two sensors. Secondly, the study sought to map the spatial distribution of invasive water hyacinth in the river system over time (Seasonal). Multi-date 10 m Sentinel-2 MSI images were used to detect and monitor the seasonal distribution and variations of water hyacinth in the Greater Letaba River system. The study demonstrated that, about 63.82% of the river system was infested with water hyacinth during the wet season and 28.34% during the dry season. Sentinel-2 MSI managed to depict species spatio-temporal distribution with an OA of 80.79% during wet season and 79.04% in dry season, using integrated spectral bands and vegetation indices. New generation sensors provide new opportunities and potential for seasonal or long-term monitoring of aquatic invasive species like water hyacinth- a previously challenging task with broadband multispectral sensors.