Detection and mapping the spatial distribution of bracken fern weeds using the Landsat 8 OLI new generation sensor |
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| Institution: | 1. Department of Geography, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209 Pietermaritzburg, South Africa;2. Department of Geography & Environmental Studies, University of Limpopo, Private Bag X1106, Sovenga, 0727, South Africa;1. Discipline of Geography, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, P/Bag X01, Scottsville, Pietermaritzburg 3209, South Africa;2. Department of Geography & Environmental Studies, University of Limpopo, Private Bag X1106, Sovenga 0727, South Africa;3. Physics Department, University of Zimbabwe, P. O Box MP167 Mount Pleasant, Harare, Zimbabwe;1. Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Am Kirchtor 1, D-06108 Halle, Germany;2. Senckenberg Biodiversity and Climate Research Centre (BiK-F), Senckenberganlage 25, D-60325 Frankfurt (Main), Germany;3. Herbario Nacional de Bolivia (LPB) – Instituto de Ecología – MNHN, Universidad Mayor de San Andrés, Campus Universitario Cota Cota, Calle 27, La Paz, Bolivia;4. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, D-04103 Leipzig, Germany;1. University of KwaZulu-Natal, School of Agricultural, Earth and Environmental Sciences, P. Bag X01, Scottsville, 3209 Pietermaritzburg, South Africa;2. University of the Witwatersrand, School of Geography, Archaeology and Environmental Studies, P. Bag 3, Wits, 2050 Johannesburg, South Africa;3. South African National Space Agency (SANSA), SANSA Earth Observation, Pretoria 0087, P.O Box 484, Silverton, 0127, South Africa;1. Department of Technology, Metropolitan University College, Denmark;2. Department of Plant and Soil Science, School of Biological Sciences, University of Aberdeen, Scotland, United Kingdom;3. Department of Plant and Environmental Sciences, University of Copenhagen, Denmark;1. Department of Spatial Sciences, Curtin University, GPO Box U1987, Perth, WA 6845, Australia;2. Department of Environment and Agriculture, Curtin University, GPO Box U1987, Perth, WA 6845, Australia;3. CITIC Pacific Mining, GPO Box 2732, Perth, WA 6001, Australia;4. CSIRO Biosecurity Flagship, PO Box 2583, Brisbane, Qld 4001, Australia |
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| Abstract: | Bracken fern is an invasive plant that presents serious environmental, ecological and economic problems around the world. An understanding of the spatial distribution of bracken fern weeds is therefore essential for providing appropriate management strategies at both local and regional scales. The aim of this study was to assess the utility of the freely available medium resolution Landsat 8 OLI sensor in the detection and mapping of bracken fern at the Cathedral Peak, South Africa. To achieve this objective, the results obtained from Landsat 8 OLI were compared with those derived using the costly, high spatial resolution WorldView-2 imagery. Since previous studies have already successfully mapped bracken fern using high spatial resolution WorldView-2 image, the comparison was done to investigate the magnitude of difference in accuracy between the two sensors in relation to their acquisition costs. To evaluate the performance of Landsat 8 OLI in discriminating bracken fern compared to that of Worldview-2, we tested the utility of (i) spectral bands; (ii) derived vegetation indices as well as (iii) the combination of spectral bands and vegetation indices based on discriminant analysis classification algorithm. After resampling the training and testing data and reclassifying several times (n = 100) based on the combined data sets, the overall accuracies for both Landsat 8 and WorldView-2 were tested for significant differences based on Mann-Whitney U test. The results showed that the integration of the spectral bands and derived vegetation indices yielded the best overall classification accuracy (80.08% and 87.80% for Landsat 8 OLI and WorldView-2 respectively). Additionally, the use of derived vegetation indices as a standalone data set produced the weakest overall accuracy results of 62.14% and 82.11% for both the Landsat 8 OLI and WorldView-2 images. There were significant differences {U (100) = 569.5, z = ?10.8242, p < 0.01} between the classification accuracies derived based on Landsat OLI 8 and those derived using WorldView-2 sensor. Although there were significant differences between Landsat and WorldView-2 accuracies, the magnitude of variation (9%) between the two sensors was within an acceptable range. Therefore, the findings of this study demonstrated that the recently launched Landsat 8 OLI multispectral sensor provides valuable information that could aid in the long term continuous monitoring and formulation of effective bracken fern management with acceptable accuracies that are comparable to those obtained from the high resolution WorldView-2 commercial sensor. |
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| Keywords: | Bracken fern Classification accuracy Invasion Remote sensing Discrimination Encroachment Local and regional scales Rangeland productivity |
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