dc.description.abstract |
Water hyacinth (Eichhornia crassipes) is recognized as the most notorious invasive
species over the world. Although its threats and effects are fully documented, its
distribution is not yet understood, especially in complex environments, such as river
systems. Thus, this study was aimed at mapping and understanding the spatio-temporal
distribution of invasive water hyacinth in Lake Tana, using Landsat 8 OLI and Sentinel-2
MSI satellite. Training samples were collected for classification (i.e., with Maximum
likelihood classification algorithm) of the satellite images and accuracy assessment.
Image preprocessing like image enhancement was carried out before classification.
Maximum likelihood classification algorithm Supervised image classification technique
was applied to map spatio- temporal distribution of water hyacinth. The classification
accuracy assessment result for 2020 was 96% overall accuracy and 0.95 kappa
coefficient. The result indicated that water hyacinth cover 146.6 ha in 2014, 144.4 ha in
2016, 162.9ha in 2018 and 248.3ha in 2020. Between 2014 and 2016, the coverage of the
invasive weed has reduced (0.5%) but increased through 2016 and 2020 periods (2.43%).
Since the expansion of the weed is extremely fast and a problem for the eco hydrology of
the lake, therefore appropriate intervention mechanisms should be urgently introduced.
Keywords: invasive weed, Lake Tana, mapping, remote sensing, water hyacinth |
en_US |