Abstract
Efficient detection and monitoring procedures of invasive plant species are required. It is of crucial importance to deal with such plants in aquatic ecosystems, since they can affect biodiversity and, ultimately, ecosystem function and services. In this study, it is intended to detect water hyacinth (Eichhornia crassipes) using multispectral data with different spatial resolutions. For this purpose, high-resolution data (<0.1 m) acquired from an unmanned aerial vehicle (UAV) and coarse-resolution data (10 m) from Sentinel-2 MSI were used. Three areas with a high incidence of water hyacinth located in the Lower Mondego region (Portugal) were surveyed. Different classifiers were used to perform a pixel-based detection of this invasive species in both datasets. From the different classifiers used, the results were achieved by the random forest classifiers stand-out (overall accuracy (OA): 0.94). On the other hand, support vector machine performed worst (OA: 0.87), followed by Gaussian naive Bayes (OA: 0.88), k-nearest neighbours (OA: 0.90), and artificial neural networks (OA: 0.91). The higher spatial resolution from UAV-based data enabled us to detect small amounts of water hyacinth, which could not be detected in Sentinel-2 data. However, and despite the coarser resolution, satellite data analysis enabled us to identify water hyacinth coverage, compared well with a UAV-based survey. Combining both datasets and even considering the different resolutions, it was possible to observe the temporal and spatial evolution of water hyacinth. This approach proved to be an effective way to assess the effects of the mitigation/control measures taken in the study areas. Thus, this approach can be applied to detect invasive species in aquatic environments and to monitor their changes over time.
Highlights
Invasive alien species (IAS) are one of the greatest threats to biodiversity and, the continuity of ecosystem services [1]
To perform a characterization of the spectral response of the water hyacinth to the various bands acquired by unmanned aerial vehicle (UAV), 25 polygons with measurements of 0.5 m × 0.5 m were created in each of the three areas analyzed, and possible differences in plant reflectance between areas were created
By analyzing the spectral reflectance obtained from the UAV-based multispectral data (Figure 3), it can be said that it is in line with the behavior presented by green vegetation with some leaf density [36]
Summary
Invasive alien species (IAS) are one of the greatest threats to biodiversity and, the continuity of ecosystem services [1]. Water hyacinth (Eichhornia crassipes) is considered one of the most aggressive and prevalent invasive plant species. It has been ranked as one of the top 100 exotic species with the highest invasion potential in the world [6]. It is a native of the Amazon basin that has spread globally since the late 19th century due to its ornamental value and is present on all continents except Antarctica [7,8]. In Portugal, water hyacinth’s first sighting occurred in 1939 in the Tagus basin [9], and nowadays, it is present in almost all mainland regions (“Minho”, “Douro Litoral”, “Beira Litoral”, “Estremadura e Ribatejo”, “Alentejo”, and “Algarve”), even on the island of Azores (“Terceira”) [9,10,11]
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