An innovative, fast method for landslide susceptibility mapping using GIS-based LSAT toolbox
In this study, landslide susceptibility maps (LSM) of the Akıncılar region were produced with the methods of frequency ratio (FR), information value (IV), logistic regression (LR), random forest (RF), and multi-layer perceptron (MLP) by using a new GIS-based toolbox (LSAT, Landslide Susceptibility A...
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| Vydané v: | Environmental earth sciences Ročník 80; číslo 6; s. 217 |
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| Médium: | Journal Article |
| Jazyk: | English |
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Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2021
Springer Nature B.V |
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| ISSN: | 1866-6280, 1866-6299 |
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| Abstract | In this study, landslide susceptibility maps (LSM) of the Akıncılar region were produced with the methods of frequency ratio (FR), information value (IV), logistic regression (LR), random forest (RF), and multi-layer perceptron (MLP) by using a new GIS-based toolbox (LSAT, Landslide Susceptibility Assessment Tool). LSAT was used to assess the landslide susceptibility of the Akıncılar region located 150 km northwest of Sivas city (Turkey). LSM was successfully constructed using five different methods for the study area. Area under the curve (AUC) values were calculated as 70.95%, 71.85%, 72.57%, 72.67%, 73.93% for prediction rate of FR, IV, LR, MLP and RF methods, respectively. Time-consuming processes are one of the significant problems of constructing LSM. LSAT can be used easily in this type of study and minimizes such problems. Data preparation processes, visualization of modeling results, and accuracy assessment of LSM could very quickly and automatically be done thanks to this tool. |
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| AbstractList | In this study, landslide susceptibility maps (LSM) of the Akıncılar region were produced with the methods of frequency ratio (FR), information value (IV), logistic regression (LR), random forest (RF), and multi-layer perceptron (MLP) by using a new GIS-based toolbox (LSAT, Landslide Susceptibility Assessment Tool). LSAT was used to assess the landslide susceptibility of the Akıncılar region located 150 km northwest of Sivas city (Turkey). LSM was successfully constructed using five different methods for the study area. Area under the curve (AUC) values were calculated as 70.95%, 71.85%, 72.57%, 72.67%, 73.93% for prediction rate of FR, IV, LR, MLP and RF methods, respectively. Time-consuming processes are one of the significant problems of constructing LSM. LSAT can be used easily in this type of study and minimizes such problems. Data preparation processes, visualization of modeling results, and accuracy assessment of LSM could very quickly and automatically be done thanks to this tool. |
| ArticleNumber | 217 |
| Author | Polat, Ali |
| Author_xml | – sequence: 1 givenname: Ali orcidid: 0000-0002-9147-3633 surname: Polat fullname: Polat, Ali email: ali.polat@afad.gov.tr organization: Provincial Directorate of Disaster and Emergency Management of Turkey |
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| CitedBy_id | crossref_primary_10_3390_s23052549 crossref_primary_10_3389_feart_2022_872192 crossref_primary_10_1007_s00477_022_02245_8 crossref_primary_10_1016_j_apor_2024_104237 crossref_primary_10_1108_EC_07_2023_0374 crossref_primary_10_3390_rs15225427 crossref_primary_10_3390_rs14143259 crossref_primary_10_3389_feart_2022_842425 crossref_primary_10_3390_rs15225316 crossref_primary_10_1007_s11069_023_06099_3 crossref_primary_10_1007_s11069_021_04928_x crossref_primary_10_3390_ijgi12110456 crossref_primary_10_1142_S0129156425402517 crossref_primary_10_1071_WF25089 |
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| SubjectTerms | Biogeosciences Earth and Environmental Science Earth Sciences Earthquakes Environmental Science and Engineering Geochemistry Geographic information systems Geographical information systems Geology Hydrology/Water Resources Landslides Landslides & mudslides Methods Model accuracy Multilayers Original Article prediction regression analysis Support vector machines Susceptibility Terrestrial Pollution |
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| Title | An innovative, fast method for landslide susceptibility mapping using GIS-based LSAT toolbox |
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