{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T22:08:58Z","timestamp":1776982138659,"version":"3.51.4"},"reference-count":62,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T00:00:00Z","timestamp":1641945600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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\u22121 year\u22121, and only about 1% of the corridor area is susceptible to high (1.423\u20133.053 ton ha\u22121 year\u22121) and very high (3.053\u20135.854 ton ha\u22121 year\u22121) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57\u20131.65 \u03bcm) predicted the most vulnerable areas, with a very high erosivity index (0.36\u20130.95), while SWIR2 (2.11\u20132.29 \u03bcm) predicted the same regions at a high erosivity index (0.13\u20130.36). 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.<\/jats:p>","DOI":"10.3390\/rs14020348","type":"journal-article","created":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T23:17:07Z","timestamp":1642029427000},"page":"348","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Soil Erosion Susceptibility Prediction in Railway Corridors Using RUSLE, Soil Degradation Index and the New Normalized Difference Railway Erosivity Index (NDReLI)"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1163-0385","authenticated-orcid":false,"given":"Yashon O.","family":"Ouma","sequence":"first","affiliation":[{"name":"Department of Civil Engineering, University of Botswana, Private Bag UB, Gaborone 0061, Botswana"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lone","family":"Lottering","sequence":"additional","affiliation":[{"name":"Department of Civil Engineering, University of Botswana, Private Bag UB, Gaborone 0061, Botswana"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryutaro","family":"Tateishi","sequence":"additional","affiliation":[{"name":"Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi, Inage, Chiba 263-8522, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"\u00d6z\u015fahin, E., Duru, U., and Ero\u011flu, I. (2018). Land Use and Land Cover Changes (LULCC), a Key to Understand Soil Erosion Intensities in the Maritsa Basin. Water, 10.","DOI":"10.3390\/w10030335"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"21994","DOI":"10.1073\/pnas.2001403117","article-title":"Land use and climate change impacts on global soil erosion by water (2015\u20132070)","volume":"117","author":"Borrelli","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.geomorph.2017.04.038","article-title":"Mapping soil erosion hotspots and assessing the potential impacts of land management practices in the highlands of Ethiopia","volume":"292","author":"Tamene","year":"2017","journal-title":"Geomorphology"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Pal, S., Arabameri, A., Blaschke, T., Chowdhuri, I., Saha, A., Chakrabortty, R., Lee, S., and Band, S. (2020). Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility. Remote Sens., 12.","DOI":"10.3390\/rs12223675"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chalise, D., Kumar, L., and Kristiansen, P. (2019). Land Degradation by Soil Erosion in Nepal: A Review. Soil Syst., 3.","DOI":"10.3390\/soilsystems3010012"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1007\/s00267-014-0281-3","article-title":"Seasonality of Soil Erosion under Mediterranean Conditions at the Alqueva Dam Watershed","volume":"54","author":"Ferreira","year":"2014","journal-title":"Environ. Manag."},{"key":"ref_7","first-page":"8","article-title":"Quantification of areal extent of soil erosion in dryland urban areas: An example from Windhoek, Namibia","volume":"10","author":"Shikangalah","year":"2017","journal-title":"Cities Environ. (CATE)"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"953","DOI":"10.1016\/j.gsf.2015.10.007","article-title":"Assessment of soil erosion by RUSLE model using remote sensing and GIS\u2014A case study of Nethravathi Basin","volume":"7","author":"Ganasri","year":"2016","journal-title":"Geosci. Front."},{"key":"ref_9","unstructured":"Food and Agriculture Organization of the United Nations, and Intergovernmental Technical Panel on Soils (2015). Status of the World\u2019s Soil Resources (SWSR)\u2013Main Report, Food and Agriculture Organization of the United Nations and Intergovernmental Technical Panel on Soils."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1038\/s41467-017-02142-7","article-title":"An assessment of the global impact of 21st century land use change on soil erosion","volume":"8","author":"Borrelli","year":"2017","journal-title":"Nat. Commun."},{"key":"ref_11","unstructured":"IPCC (2019). Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse gas Fluxes in Terrestrial Ecosystems\u2014Summary for Policy Makers, IPCC. Report."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1016\/S1364-8152(03)00078-1","article-title":"A review of erosion and sediment transport models","volume":"18","author":"Merritt","year":"2003","journal-title":"Environ. Model. Softw."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.jhydrol.2011.12.009","article-title":"A RUSLE approach to model suspended sediment load in the Lo river (Vietnam): Effects of reservoirs and land use changes","volume":"422\u2013423","author":"Ranzi","year":"2012","journal-title":"J. Hydrol."},{"key":"ref_14","unstructured":"Wischmeier, W.H., and Smith, D.D. (1978). Predicting Rainfall Erosion Losses: A Guide to Conservation Planning, Department of Agriculture, Science and Education Administration. No. 537."},{"key":"ref_15","unstructured":"Renard, K.G. (1997). Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE)."},{"key":"ref_16","first-page":"34","article-title":"WEPP: A new generation of erosion prediction technology","volume":"46","author":"Laflen","year":"1991","journal-title":"J. Soil Water Conserv."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1111\/j.1752-1688.1998.tb05961.x","article-title":"Large area hydrologic modeling and assessment, part 1: Model development","volume":"34","author":"Arnold","year":"1998","journal-title":"J. Am. Water Resources Assoc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1016\/j.aqpro.2015.02.168","article-title":"Simulation of Sediment Yield Over Un-gauged Stations Using MUSLE and Fuzzy Model","volume":"4","author":"Kumar","year":"2015","journal-title":"Aquat. Procedia"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"889","DOI":"10.14358\/PERS.69.8.889","article-title":"Mapping Multiple Variables for Predicting Soil Loss by Geostatistical Methods with TM Images and a Slope Map","volume":"69","author":"Wang","year":"2003","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Raza, A., Ahrends, H., Habib-Ur-Rahman, M., and Gaiser, T. (2021). Modeling Approaches to Assess Soil Erosion by Water at the Field Scale with Special Emphasis on Heterogeneity of Soils and Crops. Land, 10.","DOI":"10.3390\/land10040422"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2303","DOI":"10.1007\/s40808-020-00814-w","article-title":"Evaluation of WEPP and EPM for improved predictions of soil erosion in mountainous watersheds: A case study of Kangir River basin, Iran","volume":"6","author":"Ahmadi","year":"2020","journal-title":"Model. Earth Syst. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1002\/ldr.634","article-title":"Mapping soil erosion risk in Rond\u00f4nia, Brazilian Amazonia: Using RUSLE, remote sensing and GIS","volume":"15","author":"Lu","year":"2004","journal-title":"Land Degrad. Dev."},{"key":"ref_23","first-page":"372","article-title":"Regional soil erosion risk assessment in Hai Basin","volume":"15","author":"Li","year":"2011","journal-title":"Yaogan Xuebao J. Remote Sens."},{"key":"ref_24","first-page":"440","article-title":"Factors controlling gully development: Comparing continuous and discontinuous gullies","volume":"23","author":"Sumner","year":"2011","journal-title":"Land Degrad. Dev."},{"key":"ref_25","unstructured":"US Department of Agriculture (USDA) (2006). Soil Quality\u2014Urban Technical Note No. 1, Erosion and Sedimentation on Construction Sites."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"17815","DOI":"10.1038\/s41598-018-36202-9","article-title":"Use of the Normalized Difference Road Landside Index (NDRLI)-based method for the quick delineation of road-induced landslides","volume":"8","author":"Zhao","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_27","unstructured":"Ilienko, T., Tarariko, O., Syrotenko, O., and Kuchma, T. (2021, November 24). Merging Remote and In-Situ Land Degradation Indicators in Soil Erosion Control System. Available online: http:\/\/ekmair.ukma.edu.ua\/handle\/123456789\/17305."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1080\/03736245.2020.1716838","article-title":"Soil erosion risk assessment in the Umzintlava catchment (T32E), Eastern Cape, South Africa, using RUSLE and random forest algorithm","volume":"103","author":"Phinzi","year":"2020","journal-title":"S. Afr. Geogr. J."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Panda, S.S., Masson, E., Sen, S., Kim, H.W., and Amatya, D.M. (2016). Geospatial technology applications in forest hydrology. For. Hydrol. Processes Manag. Assess., 162\u2013179.","DOI":"10.1079\/9781780646602.0162"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"012013","DOI":"10.1088\/1742-6596\/1381\/1\/012013","article-title":"Analysis of Vegetation Indices Using Metric Landsat-8 Data to Identify Tree Cover Change in Riau Province","volume":"Volume 280","author":"Kartika","year":"2019","journal-title":"IOP Conference Series: Earth and Environmental Science"},{"key":"ref_31","first-page":"12","article-title":"Urban land surface temperature variations with LULC, NDVI and NDBI in semi-arid urban environments: Case study of Gaborone City, Botswana (1989\u20132019)","volume":"Volume 11864","author":"Ouma","year":"2021","journal-title":"Remote Sensing Technologies and Applications in Urban Environments VI"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/0022-1694(94)90110-4","article-title":"Using monthly precipitation data to estimate the R-factor in the revised USLE","volume":"157","author":"Renard","year":"1994","journal-title":"J. Hydrol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.jhydrol.2011.09.022","article-title":"Rainfall erosivity in Central Chile","volume":"410","author":"Bonilla","year":"2011","journal-title":"J. Hydrol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Wang, R., Zhang, S., Yang, J., Pu, L., Yang, C., Yu, L., Chang, L., and Bu, K. (2016). Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China. Sustainability, 8.","DOI":"10.3390\/su8040317"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.catena.2003.11.006","article-title":"Rainfall erosivity map for Brazil","volume":"57","year":"2004","journal-title":"Catena"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1007\/s11368-011-0356-1","article-title":"Water infiltration in urban soils and its effects on the quantity and quality of runoff","volume":"11","author":"Yang","year":"2011","journal-title":"J. Soils Sediments"},{"key":"ref_37","unstructured":"Singh, V.P. (1995). Computer Models of Watershed Hydrology, Water Resources Publications."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1007\/s00267-012-9904-8","article-title":"Determination of Soil Erosion Risk in the Mustafakemalpasa River Basin, Turkey, Using the Revised Universal Soil Loss Equation, Geographic Information System, and Remote Sensing","volume":"50","author":"Ozsoy","year":"2012","journal-title":"Environ. Manag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s00254-003-0897-8","article-title":"Soil erosion assessment and its verification using the universal soil loss equation and geo-graphic information system: A case study at Boun, Korea","volume":"45","author":"Lee","year":"2004","journal-title":"Environ. Geol."},{"key":"ref_40","unstructured":"Van der Knijff, J.M., Jones, R.J., and Montanarella, L. (2021, August 18). Soil Erosion Risk: Assessment in Europe. Available online: https:\/\/www.unisdr.org\/files\/1581_ereurnew2.pdf."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ouri, A.E., Golshan, M., Janizadeh, S., Cerd\u00e0, A., and Melesse, A.M. (2020). Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques. Land, 9.","DOI":"10.3390\/land9100368"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1080\/02757259309532181","article-title":"Remote sensing of soil color: Principles and applications","volume":"7","author":"Escadafal","year":"1993","journal-title":"Remote Sens. Rev."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"285","DOI":"10.5589\/m11-038","article-title":"Potentiels et limites des indices spectraux pour caract\u00e9riser la d\u00e9gradation des sols en milieu semi-aride","volume":"37","author":"Maimouni","year":"2011","journal-title":"Can. J. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1080\/01431169008955129","article-title":"Visible and near infrared reflectance characteristics of dry plant materials","volume":"11","author":"Elvidge","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Rasul, A., Balzter, H., Ibrahim, G.R., Hameed, H.M., Wheeler, J., Adamu, B., Ibrahim, S.A., and Najmaddin, P.M. (2018). Applying built-up and bare-soil indices from Landsat 8 to cities in dry climates. Land, 7.","DOI":"10.3390\/land7030081"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Nguyen, C.T., Chidthaisong, A., Kieu Diem, P., and Huo, L.Z. (2021). A Modified Bare Soil Index to Identify Bare Land Features during Agricultural Fallow-Period in Southeast Asia Using Landsat. Land, 10.","DOI":"10.3390\/land10030231"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Ouma, Y.O., Cheruyot, R., and Wachera, A.N. (2021). Rainfall and runoff time-series trend analysis using LSTM recurrent neural network and wavelet neural network with satellite-based meteorological data: Case study of Nzoia hydrologic basin. Complex Intell. Syst., 1\u201324.","DOI":"10.1007\/s40747-021-00365-2"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1016\/j.rse.2009.01.016","article-title":"Detection and mapping of long-term land degradation using local net production scaling: Application to Zimbabwe","volume":"113","author":"Prince","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_49","first-page":"1","article-title":"An appraisal on the progress of remote sensing applications in soil erosion mapping and monitoring","volume":"9","author":"Sepuru","year":"2018","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"17","DOI":"10.15377\/2409-9813.2014.01.01.3","article-title":"Vis-NIR Spectroscopy for Determining Physical and Chemical Soil Properties: An Application to an Area of Southern Italy","volume":"1","author":"Buttafuoco","year":"2014","journal-title":"Glob. J. Agric. Innov. Res. Dev."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"3795","DOI":"10.1080\/01431160110104638","article-title":"Land degradation and erosion risk mapping by fusion of spectrally-based information and digital geomorphometric attributes","volume":"23","author":"Haboudane","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","unstructured":"Margate, D.E., and Shrestha, D.P. (2001, January 5\u20139). The use of hyperspectral data in identifying \u2018desert-like\u2019soil surface features in Tabernas area, southeast Spain. Proceedings of the 22nd Asian Conference on Remote Sensing, Singapore."},{"key":"ref_53","unstructured":"Hill, J., Mehl, W., and Altherr, M. (2007). Land Degradation and Soil Erosion Mapping in a Mediterranean Ecosystem. Imaging Spectrometry\u2014A Tool for Environmental Observations, Springer."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1162","DOI":"10.2136\/sssaj2003.0312","article-title":"Color Attributes and Mineralogical Characteristics, Evaluated by Radiometry, of Highly Weathered Tropical Soils","volume":"69","author":"Fontes","year":"2005","journal-title":"Soil Sci. Soc. Am. J."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.pce.2016.10.001","article-title":"Assessing and mapping the severity of soil erosion using the 30-m Landsat multispectral satellite data in the former South African homelands of Transkei","volume":"100","author":"Seutloali","year":"2017","journal-title":"Phys. Chem. Earth Parts A\/B\/C"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/S0034-4257(98)00030-3","article-title":"Relationships between Satellite-Based Radiometric Indices Simulated Using Laboratory Reflectance Data and Typic Soil Color of an Arid Environment","volume":"66","author":"Mathieu","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/s40562-017-0091-6","article-title":"Soil erosion modeled with USLE, GIS, and remote sensing: A case study of Ikkour watershed in Middle Atlas (Morocco)","volume":"4","author":"Barakat","year":"2017","journal-title":"Geosci. Lett."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"11","DOI":"10.4314\/sajg.v6i1.2","article-title":"Mapping soil erosion in a quaternary catchment in Eastern Cape using geographic information system and remote sensing","volume":"6","author":"Phinzi","year":"2017","journal-title":"S. Afr. J. Geomat."},{"key":"ref_59","unstructured":"Govaerts, B., and Verhulst, N. (2021, October 12). The Normalized Difference Vegetation Index (NDVI) Greenseeker (TM) Handheld Sensor: Toward the Integrated Evaluation of Crop Management Part A: Concepts and Case Studies. Available online: https:\/\/nue.okstate.edu\/GreenSeeker\/NDVI-PartA-mayo.pdf."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"137","DOI":"10.5194\/isprs-annals-III-5-137-2016","article-title":"Mapping eroded areas on mountain grassland with terrestrial photogrammetry and object-based image analysis","volume":"3","author":"Mayr","year":"2016","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.geomorph.2011.07.003","article-title":"Object-based gully feature extraction using high spatial resolution imagery","volume":"134","author":"Shruthi","year":"2011","journal-title":"Geomorphology"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.pce.2017.01.023","article-title":"Use of Landsat series data to analyse the spatial and temporal variations of land degradation in a dispersive soil environment: A case of King Sabata Dalindyebo local municipality in the Eastern Cape Province, South Africa","volume":"100","author":"Dube","year":"2017","journal-title":"Phys. Chem. Earth Parts A\/B\/C"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/2\/348\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:28:52Z","timestamp":1760365732000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/2\/348"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,12]]},"references-count":62,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14020348"],"URL":"https:\/\/doi.org\/10.3390\/rs14020348","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,12]]}}}