| 1. Identificação | |
| Tipo de Referência | Artigo em Revista Científica (Journal Article) |
| Site | plutao.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | 8JMKD3MGP3W/4AC8AUA |
| Repositório | sid.inpe.br/plutao/2023/12.11.14.54.44 (acesso restrito) |
| Última Atualização | 2023:12.14.12.05.45 (UTC) lattes |
| Repositório de Metadados | sid.inpe.br/plutao/2023/12.11.14.54.45 |
| Última Atualização dos Metadados | 2024:01.02.17.00.36 (UTC) administrator |
| DOI | 10.1016/j.iswcr.2023.09.008 |
| ISSN | 2095-6339 |
| Rótulo | lattes: 5290642954663700 4 HitouriMAQPHLV:2023:HyDeMo |
| Chave de Citação | HitouriMAQHPEV:2023:HyDeMo |
| Título | Gully erosion mapping susceptibility in a Mediterranean environment: A hybrid decision-making model  |
| Ano | 2023 |
| Data de Acesso | 11 maio 2024 |
| Tipo de Trabalho | journal article |
| Tipo Secundário | PRE PI |
| Número de Arquivos | 1 |
| Tamanho | 9106 KiB |
| 2. Contextualização | |
| Autor | 1 Hitouri, Sliman 2 Mohajane, Meriame 3 Ali, Sk Ajim 4 Quevedo, Renata Pacheco 5 Huy, Thong Nguyen 6 Pham, Quoc Bao 7 ElKhrachy, Ismail 8 Varasano, Antonietta |
| Grupo | 1 2 3 4 SER-SRE-DIPGR-INPE-MCTI-GOV-BR |
| Afiliação | 1 University Ibn Tofail 2 National Research Council of Italy 3 Aligarh Muslim University (AMU) 4 Instituto Nacional de Pesquisas Espaciais (INPE) 5 University of Southern Queensland 6 University of Silesia in Katowice 7 Najran University 8 National Research Council |
| Endereço de e-Mail do Autor | 1 2 mohajane@itc.cnr.it 3 4 renata.quevedo@inpe.br |
| Revista | International Soil And Water Conservation Research |
| Volume | 09 |
| Páginas | 1 |
| Histórico (UTC) | 2023-12-11 14:54:45 :: lattes -> administrator :: 2023-12-12 19:19:23 :: administrator -> lattes :: 2023 2023-12-14 12:05:49 :: lattes -> administrator :: 2023 2024-01-02 17:00:36 :: administrator -> simone :: 2023 |
| 3. Conteúdo e estrutura | |
| É a matriz ou uma cópia? | é a matriz |
| Estágio do Conteúdo | concluido |
| Transferível | 1 |
| Tipo do Conteúdo | External Contribution |
| Tipo de Versão | publisher |
| Resumo | Gully erosion is one of the main natural hazards, especially in arid and semi-arid regions, destroying ecosystem service and human well-being. Thus, gully erosion susceptibility maps (GESM) are urgently needed for identifying priority areas on which appropriate measurements should be considered. Here, we proposed four new hybrid Machine learning models, namely weight of evidence -Multilayer Perceptron (MLP- WoE), weight of evidence eK Nearest neighbours (KNN- WoE), weight of evidence - Logistic regression (LR- WoE), and weight of evidence - Random Forest (RF- WoE), for mapping gully erosion exploring the opportunities of GIS tools and Remote sensing techniques in the El Ouaar watershed located in the Souss plain in Morocco. Inputs of the developed models are composed of the dependent (i.e., gully erosion points) and a set of independent variables. In this study, a total of 314 gully erosion points were randomly split into 70% for the training stage (220 gullies) and 30% for the validation stage (94 gullies) sets were identified in the study area. 12 conditioning variables including elevation, slope, plane curvature, rainfall, distance to road, distance to stream, distance to fault, TWI, lithology, NDVI, and LU/LC were used based on their importance for gully erosion susceptibility mapping. We evaluate the performance of the above models based on the following statistical metrics: Accuracy, precision, and Area under curve (AUC) values of receiver operating characteristics (ROC). The results indicate the RF- WoE model showed good accuracy with (AUC ¼ 0.8), followed by KNN-WoE (AUC ¼ 0.796), then MLP-WoE (AUC ¼ 0.729) and LR-WoE (AUC ¼ 0.655), respectively. Gully erosion susceptibility maps provide information and valuable tool for decision-makers and planners to identify areas where urgent and appropriate interventions should be applied. |
| Área | SRE |
| Arranjo 1 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Gully erosion mapping... |
| Arranjo 2 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Gully erosion mapping... |
| Conteúdo da Pasta doc | acessar |
| Conteúdo da Pasta source | não têm arquivos |
| Conteúdo da Pasta agreement | não têm arquivos |
| 4. Condições de acesso e uso | |
| Idioma | en |
| Arquivo Alvo | 1-s2.0-S2095633923000898-main.pdf |
| Grupo de Usuários | lattes |
| Grupo de Leitores | administrator lattes |
| Visibilidade | shown |
| Permissão de Leitura | deny from all and allow from 150.163 |
| Permissão de Atualização | não transferida |
| 5. Fontes relacionadas | |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/3F3NU5S 8JMKD3MGPCW/46KUATE |
| Lista de Itens Citando | sid.inpe.br/bibdigital/2013/10.18.22.34 1 |
| Divulgação | WEBSCI; SCOPUS. |
| Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notas | |
| Campos Vazios | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn keywords lineage mark mirrorrepository month nextedition notes number orcid parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url |
| 7. Controle da descrição | |
| e-Mail (login) | simone |
| atualizar | |