Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/81701
Título: | Soil erosion quantification using Machine Learning in sub-watersheds of Northern Portugal |
Autor(es): | Folharini, Saulo Oliveira Vieira, António Bento-Gonçalves, António Silva, Sara Marques, Tiago Ribeiro Novais, Jorge Leandro Ramalho |
Palavras-chave: | soil erosion sub-watersheds machine learning burned areas protected areas |
Data: | 2023 |
Editora: | Multidisciplinary Digital Publishing Institute (MDPI) |
Revista: | Hydrology |
Citação: | Folharini, S.; Vieira, A.; Bento-Gonçalves, A.; Silva, S.; Marques, T.; Novais, J. Soil Erosion Quantification using Machine Learning in Sub-Watersheds of Northern Portugal. Hydrology 2023, 10, 7. https://doi.org/10.3390/hydrology10010007 |
Resumo(s): | Protected areas (PA) play an important role in minimizing the effects of soil erosion in watersheds. This study evaluated the performance of machine learning models, specifically support vector machine with linear kernel (SVMLinear), support vector machine with polynomial kernel (SVMPoly), and random forest (RF), on identifying indicators of soil erosion in 761 sub-watersheds and PA in northern Portugal, by using soil erosion by water in Europe, according to the revised universal soil loss equation (RUSLE2015), as target variable. The parameters analyzed were: soil erosion by water in Europe according to the revised universal soil loss equation (RUSLE2015), total burned area of the sub-watershed in the period of 1975-2020, fire recurrence, topographic wetness index (TWI), and the morphometric factors, namely area (A), perimeter (P), length (L), width (W), orientation (O), elongation ratio (Re), circularity ratio (Rc), compactness coefficient (Cc), form factor (Ff), shape factor (Sf), DEM, slope, and curvature. The median coefficient of determination (R2) for each model was RF (0.61), SVMpoly (0.68), and SVMLinear (0.54). Regarding the analyzed parameters, those that registered the greatest importance were A, P, L, W, curvature, and burned area, indicating that an analysis which considers morphometric factors, together with soil erosion data affected by water and soil moisture, is an important indicator in the analysis of soil erosion in watersheds. |
Tipo: | Artigo |
Descrição: | Data Availability Statement: Soil erosion by water (RUSLE2015), available at: https://esdac.jrc.ec.europa.eu/content/soil-erosion-water-rusle2015, accessed on 21 December 2022; European Digital Elevation Model (EU-DEM), available at: https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1, accessed on 21 December 2022; Watersheds, available at: https://snig.dgterritorio.gov.pt/rndg/srv/por/catalog.search#/search?anysnig=Bacias%20Hidrogr%C3%A1ficas%20das%20Massas%20de%20%C3%81gua%20de%20Portugal%20Continental:%20CDG%20SNIAmb&fast=index, accessed on 21 December 2022; Burned areas, available at: https://sig.icnf.pt/portal/home/item.html?id=983c4e6c4d5b4666b258a3ad5f3ea5af, accessed on 21 December 2022; Protected areas, available at: https://geocatalogo.icnf.pt/catalogo_tema1.html, accessed on 21 December 2022. |
URI: | https://hdl.handle.net/1822/81701 |
DOI: | 10.3390/hydrology10010007 |
e-ISSN: | 2306-5338 |
Versão da editora: | https://www.mdpi.com/2306-5338/10/1/7 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CECS - Artigos em revistas internacionais / Articles in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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hydrology-10-00007-v2.pdf | Documento | 3,4 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons