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Kaveh Ghahraman, Balázs Nagy and Fatemeh Nooshin Nokhandan
We utilized the random forest (RF) machine learning algorithm, along with nine topographical/morphological factors, namely aspect, slope, geomorphons, plan curvature, profile curvature, terrain roughness index, surface texture, topographic wetness index ...
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Hanaa A. Megahed, Amira M. Abdo, Mohamed A. E. AbdelRahman, Antonio Scopa and Mohammed N. Hegazy
The occurrence of flash floods is a natural yet unavoidable occurrence over time. In addition to harming people, property, and resources, it also undermines a country?s economy. This paper attempts to identify areas of flood vulnerability using a frequen...
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Saulo Folharini, António Vieira, António Bento-Gonçalves, Sara Silva, Tiago Marques and Jorge Novais
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 machi...
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Hugo Leonardo Oliveira Chaves,Maria Elisa Leite Costa,Sérgio Koide,Tati de Almeida,Rejane Ennes Cicerelli
Pág. 148 - 166
O mapeamento de suscetibilidade à inundação é importante para o manejo da dinâmica do uso do solo e, consequentemente, da hidrologia urbana local. O presente estudo produziu o mapa de suscetibilidade à inundação na Bacia do Riacho Fundo, Distrito Federal...
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Yasin Wahid Rabby and Yingkui Li
Landslide susceptibility mapping is of critical importance to identify landslide-prone areas to reduce future landslides, causalities, and infrastructural damages. This paper presents landslide susceptibility maps at a regional scale for the Chittagong H...
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Wei Chen, Zenghui Sun, Xia Zhao, Xinxiang Lei, Ataollah Shirzadi and Himan Shahabi
The purpose of this study is to compare nine models, composed of certainty factors (CFs), weights of evidence (WoE), evidential belief function (EBF) and two machine learning models, namely random forest (RF) and support vector machine (SVM). In the firs...
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Azam Kadirhodjaev, Fatemeh Rezaie, Moung-Jin Lee and Saro Lee
Landslides can cause considerable loss of life and damage to property, and are among the most frequent natural hazards worldwide. One of the most fundamental and simple approaches to reduce damage is to prepare a landslide hazard map. Accurate prediction...
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Tung Gia Pham, Martin Kappas, Chuong Van Huynh and Linh Hoang Khanh Nguyen
Soil property maps are essential resources for agricultural land use. However, soil properties mapping is costly and time-consuming, especially in the regions with complicated topographic conditions. This study was conducted in a hilly region of Central ...
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Ljubomir Gigovic, Sini?a Drobnjak and Dragan Pamucar
The main goal of this article is to produce a landslide susceptibility map by using the hybrid Geographical Information System (GIS) spatial multi-criteria decision analysis best?worst methodology (MCDA-BWM) in the western part of the Republic of Serbia....
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Xiaoyi Shao, Chong Xu, Siyuan Ma and Qing Zhou
The seismogenic fault is crucial for spatial prediction of co-seismic landslides, e.g., in logistic regression (LR) analysis considering influence factors. On one hand, earthquake-induced landslides are usually densely distributed along the seismogenic f...
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