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Susceptibility mapping of linear erosion processes using object-based analysis of VHR images

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Passo, D.P. and Bias, E.S. and Brites, R.S. and Costa, G.A.O.P. and Antunes, R.R. (2016) Susceptibility mapping of linear erosion processes using object-based analysis of VHR images. In: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC) .

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Event: GEOBIA 2016 : Solutions and Synergies., 14 September 2016 - 16 September 2016, University of Twente Faculty of Geo-Information and Earth Observation (ITC)
Abstract:Linear erosion is a natural phenomenon. However, inadequate occupation of the environment or the implementation of engineering works, without the due care, accelerates this process, which has been acknowledged as the main cause of land degradation worldwide. The use of high-resolution satellite imaging to map risk areas for this process, may contribute to devising prevention strategies. Linear erosion is a process dependent on thresholds controlled by many variables. This study has used only topographic variables (altimetry, slope, curvature profile, curvature plan, slope orientation, accumulation flow, humidity index, sediment transport capacity, potential flow and drainage network) and a vegetation index, which were selected due to their influence on linear erosion processes. The study was developed in two 6,000 x 4,500 meter areas, located in the eastern part of the Federal District – Brazil. The classification model building was done using open source software packages, namely InterIMAGE and WEKA. The aim of this study was to develop a routine for automatic mapping of areas susceptible to linear erosion. The accuracy rate achieved by the model was 87.5%, as 21 of 24 linear erosion processes were identified. The percentage of the mapped area in relation to the total study area also showed that the classification was not overestimated.
Item Type:Conference or Workshop Item (Paper)
Link to this item:https://doi.org/10.3990/2.434
Conference URL:https://www.geobia2016.com/
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