Impact of Vegetation Differences on Shallow Landslides: A Case Study in Aso, Japan

Abstract

Climate change has increased the frequency and scale of heavy rainfall, increasing the risk of shallow landslides due to heavy rainfall. In recent years, ecosystem-based disaster risk reduction (Eco-DRR) has attracted attention as one way to reduce disaster risks. Vegetation is known to increase soil strength through its root system and reduce the risk of shallow landslides. To reduce the risk of shallow landslides using vegetation, it is necessary to quantitatively evaluate the effects that vegetation has on shallow landslides. In this study, we constructed a generalized linear model (GLM) and random forest (RF) model to quantitatively evaluate the impact of differences in the vegetation, such as grasslands and forests, on the occurrence of shallow landslides using statistical methods. The model that resulted in the lowest AIC in the GLM included elevation, slope angle, slope aspect, undulation, TWI, geology, and vegetation as primary factors, and the hourly rainfall as a trigger factor. The slope angle, undulation, and hourly rainfall were selected as significant explanatory variables that contribute positively to shallow landslides. On the other hand, elevation and TWI were selected as significant explanatory variables that contribute negatively to shallow landslides. Significant differences were observed among multiple categories of vegetation. The probability of shallow landslide in secondary grasslands was approximately three times that of coniferous and broadleaf forests, and approximately nine times that of broadleaf secondary forests. The landslide probability of shrubs was approximately four times that of coniferous and broadleaf forests, and approximately ten times that of broadleaf secondary forests. The results of constructing the RF model showed that the importance was highest for the hourly rainfall, followed by geology, then elevation. AUC values for the GLM and RF model were 0.91 and 0.95, respectively, indicating that highly accurate models were constructed. We quantitatively showed the impact of differences in vegetation on shallow landslides. The knowledge obtained in this study will be essential for considering appropriate vegetation management to reduce the risk of future shallow landslides.

Study on Spatial and Temporal Changes in Landscape Ecological Risks and Indicator Weights: A Case Study of the Bailong River Basin

“…Since the total area of these two land types is not large, they are not focused on in this paper. Dry land (12) dominates the cultivated land in the basin, and the urban scale is small except for the urban land (51) of Longnan City in the center of the river basin, which has increased piecemeal. On the contrary, in the rural residential areas (52) on both sides of the river, new rural residential areas are developing rapidly, and the rural residential areas are intertwined with the dry field in the form of dots.…”

“…It is difficult to distinguish the mutual influence of risk among different factors [8,9]. The landscape index method focuses on the ecological risk effect of the degree of deviation of the landscape mosaic relative to the optimal pattern [10][11][12]. The current study uses the landscape index method as the primary evaluation method for LER.…”

Study on surface deformation pattern in mine closure area of complex karst mountainous region based on SBAS-InSAR technology

“…Additionally, elevation plays a role in determining the types of vegetation covering the surface. Different vegetation types exert diverse effects on slope stability (Asada and Minagawa, 2023). Consequently, this study places particular emphasis on investigating the interconnected relationship between surface deformation, elevation variations, slope characteristics, vegetation distribution, and precipitation patterns following mine closures within karst regions.…”

“…Similarly, Qian et al (2022) conducted a susceptibility analysis of landslides in Liupanshui, employing various geographical factors and a Logistic fuzzy comprehensive coupling model on a Geographic Information System (GIS) platform. Their results In their more recent study (Asada and Minagawa, 2023), they constructed generalized linear models (GLM) and random forest models (RF) using statistical methods to quantitatively assess the impact of different vegetation conditions on shallow landslide occurrence. The models were developed considering slope and hourly precipitation as critical parameters for evaluating slope stability.…”

Landscape Ecological Risk Evaluation Study under Multi-Scale Grids—A Case Study of Bailong River Basin in Gansu Province, China

“…Strengthening the evaluation of LERI, preventing and resolving major ecological and environmental risks, and improving the early warning ability of LERI are priority tasks for the construction of ecological civilization [20]. In general, commonly used assessment methods for the LERI are the risk source and sink method and the landscape index method, which are fundamentally based on the probability multiplied by the loss to calculate the risk.…”