Assessing the potential of remote sensing to discriminate invasive Seriphium plumosum from grass

The usefulness of remote sensing to discriminate Seriphium plumosum from grass using a field spectrometer data was investigated in this study. Analysis focused on wavelength regions that showed potential of discriminating S. plumosum from grass which were determined from global pair spectral comparison between S. plumosum and grass. Assessment of reflectance differences done at individual and plot levels using original spectra and spectra simulated based on bands of Landsat and SPOT 5 images. The simulations were done to investigate the possibility of extending field based information into airborne and spaceborne remote sensing techniques. Results showed reflectance spectra of S. plumosum and grass to be relatively comparable. Comparisons at all levels of analysis using original spectra did not show noteworthy reflectance difference in all regions used in the analysis. Similarly, simulated spectra did not show significant differences. The results therefore did not appear to encourage the potential of upscaling the application to airborne and spaceborne remote sensing techniques. There were, however, some shortcomings that made it difficult to draw conclusive remarks on whether the plant can be differentiated from grass. These included, firstly, not all species were in the same phenology. Secondly, spectral measurements were not necessarily taken in an ideal scenario of optimal sunny conditions. It is therefore advised that a similar study be carried out that will address the shortcomings of this study. Furthermore, studies on the biochemical composition of both S. plumosum and grass species are needed, since they explain spectral properties of plants

Characterizing selected invasive plants in the Klipriviersberg Nature Reserve using field based spectroradiometer data

Abstract: The Klipriviersberg Nature Reserve has proportionally large number of invasive plant species (Morné Britz, personal communication). Management of these species currently focuses on conspicuous woody species and less attention is placed on smaller plant species that are likely to threaten biodiversity. This can potentially result in more costly and labour intensive management programmes if imminent environmental threats are not timeously identified. The use of timely spatial distribution maps aids in improving invasive plant management strategies. Invasive plant distribution maps have been developed using traditional mapping methods; but these are costly and time consuming. Remote sensing techniques on the other hand have shown the potential in characterizing invasive plants species in different studies. This study aimed to extend this potential by discriminating selected invasive plant species, namely, Artemisia afra, Asparagus laricinus and Seriphium plumosum from adjacent land cover types using continuum spectra of a field spectrometer data. In addition, the study aimed to investigate the use of spectra simulated according to bands of SPOT and Landsat images in an effort to explore the potential of extending field based analysis to airborne or spaceborne remote sensing systems. Data were analysed at individual, plot and group levels, respectively. Results showed A. afra and A. laricinus to be best discriminated from adjacent land cover types using the near infrared (NIR) region from analysis using both original and simulated spectra. None of the regions that were assessed for S. plumosum, however, did show the potential of discriminating the species from grass using both the original and simulated spectra. Successful discrimination of A. afra and A. laricinus from adjacent land cover types using simulated bands shows the potential of upscaling field based techniques, particularly the NIR region, to spaceborne and airborne remote sensing technologies such as SPOT and Landsat. Further studies are, however, recommended to improve the reliability of the findings obtained in this study. Such studies would need to address the shortcomings encountered in this study by (1) using more samples, (2) categorising data analysis according to plant phonological stages to help determine best timing for discrimination of the species, and (3) taking of spectral measurements under ideal environmental conditions. Studies on biochemical composition of the species are also encouraged to inform on reflectance behaviours of the species as plant compounds or pigments influence electromagnetic reflectance differently.M.Sc

Field spectroradiometer and simulated multispectral bands for discriminating invasive species from morphologically similar cohabitant plants

One of the challenges in fighting plant invasions is the inefficiency of identifying their distribution using field inventory techniques. Remote sensing has the potential to alleviate this problem effectively using spectral profiling for species discrimination. However, little is known about the capability of remote sensing in discriminating between shrubby invasive plants with narrow leaf structures and other cohabitants with similar ecological niche. The aims of this study were therefore to (1) assess the classification performance of field spectroradiometer data among three bushy and shruby plants (Artemesia afra, Asparagus laricinus, and Seriphium plumosum) from the coexistent plant species largely dominated by acacia and grass species, and (2) explore the performance of simulated spectral bands of five space-borne images (Landsat 8, Sentinel 2A, SPOT 6, Pleiades 1B, and WorldView-3). Two machine-learning classifiers (boosted trees classification and support vector machines) were used to classify raw hyperspectral (n = 688) and simulated multispectral wavelengths. Relatively high classification accuracies were obtained for the invasive species using the original hyperspectral bands for both classifiers (overall accuracy, OA = 83–97%). The simulated data resulted in higher accuracies for Landsat 8, Sentinel 2A, and WorldView-3 compared to those computed for bands simulated to SPOT 6 and Pleiades 1B data. These findings suggest the potential of remote-sensing techniques in the discrimination of different plant species with similar morphological characteristics occupying the same niche