| 1. Identity statement | |
| Reference Type | Journal Article |
| Site | plutao.sid.inpe.br (namespace prefix: upn:33M4QT8) |
| Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identifier | 8JMKD3MGP3W/474NTKP |
| Repository | sid.inpe.br/plutao/2022/06.15.12.26 (restricted access) |
| Last Update | 2022:06.20.17.51.41 (UTC) lattes |
| Metadata Repository | sid.inpe.br/plutao/2022/06.15.12.26.03 |
| Metadata Last Update | 2023:01.03.16.52.55 (UTC) administrator |
| DOI | 10.1007/s12517-022-09488-3 |
| ISSN | 1866-7511 |
| Label | lattes: 7712719010541171 9 ZhangQWFLWOGR:2022:ImTrMa |
| Citation Key | ZhangQWFLWOGR:2022:ImTrMa |
| Title | Improved tree-based machine learning algorithms combining with bagging strategy for landslide susceptibility modeling  |
| Year | 2022 |
| Access Date | 2025, Dec. 08 |
| Type of Work | journal article |
| Secondary Type | PRE PI |
| Number of Files | 1 |
| Size | 3168 KiB |
| 2. Context | |
| Author | 1 Zhang, Tingyu 2 Quevedo, Renata Pacheco 3 Wang, Huanyuan 4 Fu, Quan 5 Luo, Dan 6 Wang, Tao 7 Oliveira, Guilherme Garcia de 8 Guasselli, Laurindo Antonio 9 Rennó, Camilo Daleles |
| Resume Identifier | 1 2 3 4 5 6 7 8 9 8JMKD3MGP5W/3C9JGN2 |
| Group | 1 2 SER-SRE-DIPGR-INPE-MCTI-GOV-BR 3 4 5 6 7 8 9 DIOTG-CGCT-INPE-MCTI-GOV-BR |
| Affiliation | 1 Key Laboratory of Degraded and Unused Land Consolidation Engineering 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Key Laboratory of Degraded and Unused Land Consolidation Engineering 4 Shaanxi Provincial Land Engineering Construction Group Land Survey Planning, Design Institute Co 5 Shaanxi Provincial Land Engineering Construction Group Land Survey Planning, Design Institute Co 6 Shaanxi Provincial Land Engineering Construction Group Land Survey Planning, Design Institute Co 7 Universidade Federal do Rio Grande do Sul (UFRGS) 8 Universidade Federal do Rio Grande do Sul (UFRGS) 9 Instituto Nacional de Pesquisas Espaciais (INPE) |
| Author e-Mail Address | 1 2 renatapquevedo@gmail.com 3 4 5 6 7 8 9 camilo.renno@inpe.br |
| Journal | Arabian Journal of Geosciences |
| Volume | 15 |
| Number | 2 |
| Pages | 183 |
| History (UTC) | 2022-06-15 12:50:27 :: lattes -> administrator :: 2022 2022-06-17 07:44:40 :: administrator -> lattes :: 2022 2022-06-20 17:51:42 :: lattes -> administrator :: 2022 2023-01-03 16:52:55 :: administrator -> simone :: 2022 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Content Type | External Contribution |
| Version Type | publisher |
| Keywords | Landslide susceptibility · Decision tree · Logistic model tree · Reduced error pruning tree · Hybrid models · Bagging strategy |
| Abstract | Landslide is considered one of the most dangerous natural hazards. Reasonable landslide susceptibility mapping can aid decision makers in landslide prevention. For this reason, based on the feld survey data of landslide in Chenggu County, Shaanxi Province, China, 15 conditioning factors (altitude, slope, aspect, plan curvature, profle curvature, SPI, TWI, distance to roads, distance to rivers, distance to faults, rainfall, NDVI, soil, lithology, and land use) were selected and quantifed by the certainty factor index. Then, 184 landslides data were divided into training and validation datasets according to the ratio of 7/3. Based on the GIS platform, three hybrid tree-based models, namely decision tree (DT), logistic model tree (LMT), and reduced error pruning tree (REPT), were established. Additionally, the bagging method was applied to build three baghybrid tree-based models: Bag-DT, Bag-LMT, and Bag-REPT. Finally, the landslide susceptibility maps were produced, and statistical indexes, seed cell area index and the ROC curve, were used for model validation and comparison. The results showed that the bagging method can signifcantly improve the classifcation ability of hybrid models. Furthermore, the BagREPT presented the best performance, with an accuracy value of 92.5%, being a suitable model for landslide susceptibility mapping in the study area. |
| Area | SRE |
| Arrangement 1 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Improved tree-based machine... |
| Arrangement 2 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Improved tree-based machine... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| Language | en |
| Target File | Zhang2022_Article_ImprovedTree-basedMachineLearn.pdf |
| Reader Group | administrator lattes |
| Visibility | shown |
| Read Permission | deny from all and allow from 150.163 |
| Update Permission | not transferred |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPCW/3F3NU5S 8JMKD3MGPCW/46KUATE |
| Citing Item List | sid.inpe.br/bibdigital/2022/04.03.22.23 - 42 sid.inpe.br/bibdigital/2013/10.18.22.34 - 40 sid.inpe.br/mtc-m21/2012/07.13.14.42 - 12 |
| Dissemination | WEBSCI; PORTALCAPES; SCOPUS. |
| Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notes | |
| Empty Fields | alternatejournal archivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn lineage mark mirrorrepository month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarykey secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url usergroup |
| 7. Description control | |
| e-Mail (login) | simone |
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