0000000000345367
AUTHOR
Saro Lee
showing 3 related works from this author
Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM
2021
Abstract The geomorphic studies are extremely dependent on the quality and spatial resolution of digital elevation model (DEM) data. The unique terrain characteristics of a particular landscape are derived from DEM, which are responsible for initiation and development of ephemeral gullies. As the topographic features of an area significantly influences on the erosive power of the water flow, it is an important task the extraction of terrain features from DEM to properly research gully erosion. Alongside, topography is highly correlated with other geo-environmental factors i.e. geology, climate, soil types, vegetation density and floristic composition, runoff generation, which ultimately inf…
Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
2021
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then d…
Application of the group method of data handling (GMDH) approach for landslide susceptibility zonation using readily available spatial covariates
2022
Abstract Landslide susceptibility (LS) mapping is an essential tool for landslide risk assessment. This study aimed to provide a new approach with better performance for landslide mapping and adopting readily available variables. In addition, it investigates the capability of a state-of-the-art model developed using the group method of data handling (GMDH) to spatially model LS. Furthermore, hybridized models of GMDH were developed using different metaheuristic algorithms. The study area was the Bonghwa region of South Korea, for which an accurate landslide inventory dataset is available. We considered a total of 13 spatial covariates (altitude, slope, aspect, topographic wetness index, val…