Abstract
In South Africa, soil erosion is considered as an environmental and social problem with serious financial implications particularly in some rural areas where this geomorphological phenomenon is widespread. An example is the Umzimvubu Local Municipality, where most households are strongly reliant on agriculture for their livelihood. Sustainable agriculture and proper land management in these rural areas require up-to-date and accurate information relevant to the spatial distribution of soil erosion. This study was therefore aimed at generating such information using Landsat8 Operational Land Imager (OLI)-derived vegetation indices (VIs) including the Normalised Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), as well as Soil and Atmospherically Resistance Vegetation Index (SARVI). Raster calculator in ArcMap10.2 was used to classify soil erosion features based on selected suitable thresholds in each VI. SPOT6/7 ( Systeme Pour Observation de la Terre ) multispectral data and Google Earth images were used for ground truth purposes. NDVI achieved the highest overall classification accuracy of 85% and kappa statistics of 69%, followed by SAVI with an overall accuracy and kappa statistic of 83% and 64%, respectively. SARVI produced very low overall accuracy (68%) and kappa statistic (25%) relative to other indices. Using these indices, the study successfully mapped the spatial distribution of soil erosion within the study area albeit there were some challenges due to coarser spatial resolution (30mx30m) of Landsat8 image. Due to this setback, image fusion and pan-sharpening of Landsat8 with high multispectral resolution images is strongly suggested as an alternative to improve the Landsat8 spatial resolution.
Highlights
Soil erosion is considered one of the world’s most critical environmental concerns owing to its adverse effects on both the natural environment and human society (Jie et al, 2002; Le Roux et al, 2008; Aiello et al, 2015)
The results indicate that Normalised Difference Vegetation Index (NDVI) achieved highest accuracy for producer’s accuracy (78.4%) in the erosion class (Table 1)
Soil Adjusted Vegetation Index (SAVI) outperformed other vegetation indices (VIs) with an overall accuracy of 83% and kappa statistics of 0.64 (64%)
Summary
Soil erosion is considered one of the world’s most critical environmental concerns owing to its adverse effects on both the natural environment and human society (Jie et al, 2002; Le Roux et al, 2008; Aiello et al, 2015). In financial terms, according to Scherr (1999) cited in Jie et al (2002), at least $28 billion have been lost per year due to soil degradation in drylands around the world. In South Africa, more than 70% of the land is subject to significant levels of soil erosion (Garland et al, 2000). Many soil erosion-borne studies (including Beckedhal and De Villiers, 2000; Boardman et al, 2003; Ngetar, 2011) have been conducted over the past few years in South Africa. One weakness of the South African soil erosion research is the limited information on where the problem is highly concentrated (Le Roux et al, 2007). Considerable attention has been paid to the “what” question rather than to the “where” question and this calls for more research to generate adequate information regarding the spatial distribution of the problem
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