Remote Sensing (Jan 2022)

Soil Erosion Susceptibility Prediction in Railway Corridors Using RUSLE, Soil Degradation Index and the New Normalized Difference Railway Erosivity Index (NDReLI)

  • Yashon O. Ouma,
  • Lone Lottering,
  • Ryutaro Tateishi

DOI
https://doi.org/10.3390/rs14020348
Journal volume & issue
Vol. 14, no. 2
p. 348

Abstract

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This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better than the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

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