Assessing Landslide Susceptibility by Coupling Spatial Data Analysis and Logistic Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection
2.3. Causative Factor Selection
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- Morphology. The landform is one of the most important factors influencing landslide occurrence [25]. The slope angle is considered one of the main triggering factors for landslides [26,27]. The aspect is decisive for triggering landslide processes. It is strictly connected to climatic conditions [28] and the factor impacting slope stability [29]. The topographical indices are useful for describing and quantifying the intensity and characteristics of hydrological processes [25]. The main topographical indices are reported in Table S1.
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- The topographic factors were calculated starting with a high-resolution digital terrain model (DTM) with 8-m resolution.
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- Pedology (texture). Soil texture is one of the soil’s main physical features. Previous work has shown how soils of different textures can have different levels of susceptibility to the triggering of landslides [24]. Hamza et al. (2017) indicated that limestone has more probability of landslide occurrence, thus providing a hazard index value of 1.10 (Table 2). In contrast, the probability of occurrence of landslide for gypsum and sandstone is comparatively lower, with a hazard index ranging from 0.80 to 0.77.
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- Distance from river. This parameter has a strong link to the erosion process in hilly regions [9]. Rivers and streams play an important role in landscape modification by modeling the landforms and shaping the lithological substrate [32]. The distance from the river is calculated as the Euclidean distance by the river stream extracted from a high resolution (1:10000) land use map.
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- Seismic factor. The dynamics of triggering landslides following an earthquake are well documented [33,34,35]. Earthquake-induced landslides are one of the worst natural hazards [36]. Specifically, there is a strong relationship between distance from faults and epicenters [37]. Furthermore, the factors triggering earthquake-induced landslides are also related to earthquake characteristics, such as ground acceleration [11].
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- Climate. The climate affects landslides both directly and indirectly. For instance, intense rainfall is the most common triggering agent of landslides [38].
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- Land cover/land use. It influences the ability to eventually prevent and/or limit the extent and distribution of landslides. Forested and natural systems usually showed a statistically lower landslide occurrence, and they have an important role in preventing it. This is especially true when located in areas with critical topographical and lithological conditions [39].
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- Distance from road. Roads are an important susceptibility factor to the triggering of landslides as their construction could modify the land topography and shape. As a matter of fact, roads represent an important driver of the soil profile and hillslope alteration [2].
Variable Selection
2.4. Logistic Regression
3. Results
3.1. Main Factors Affecting Slope Stability
3.2. Model Performance
3.3. Susceptibility Mapping
4. Discussion
4.1. Logistic Regression Metrics
4.2. Correlation Analysis
4.3. Perspectives
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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Landslide Type | N. |
---|---|
Slow earthflow | 228 |
Rotational/traslational landslide | 143 |
Complex landslide | 96 |
Rapid debris flow | 18 |
Fall/topple | 11 |
Area affected by numerous shallow landslide | 11 |
Unclassified landslide | 7 |
Sinkhole | 1 |
Total number | 515 |
Class of Factors | Factors Selected |
---|---|
Topography | Elevation; Flow accumulation; Planform curvature; Profile curvature; Standard curvature; Slope; Aspect; Topographic indexes (Slope roughness, Terrain roughness, Topographic wetness index, Vector Ruggedness Measure, Topographic Position Index, Topographic factor). |
Seismic Factors | Peak ground acceleration; Distance to active fault; Distance to earthquake epicenter. |
Geolithology | Percentage of cover area of Terrace alluvium; Sandstones and clays; Clays and marls; Clays; Debris; Alluvium and river-lake deposits; Beaches; Lakes and glaciers; Sands and conglomerates; Sandy and sand-marly units; Clayey and clayey-limestone units; Marly limestone units. |
Pedology | Percentage of cover area of clay; Percentage of sand; Percentage of silt. |
Land Cover | Percentage of cover area of Urban area; Agricultural area; Grassland; Forest; Natural area, Rivers and lakes. |
Morphology | Distance to rivers; Distance to roads. |
Climate | Mean annual maximum rainfall observed in 1 day; Mean annual rainfall. |
Total landslide (TL) | Rotational/Traslational Landslide (RTL) | Slow Earth Flow (SEF) | Complex Landslide (CL) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Factor | Coeff. | SE | p | Coeff. | SE | p | Coeff. | SE | p | Coeff. | SE | p |
−0.381 | 0.030 | *** | −0.704 | 0.037 | *** | −0.694 | 0.036 | *** | −0.388 | 0.031 | *** | |
T_TWI | −0.099 | 0.025 | *** | / | / | / | / | / | / | −0.207 | 0.023 | *** |
T_VRM | 0.086 | 0.023 | *** | 0.076 | 0.027 | * | / | / | / | 0.050 | 0.026 | . |
T_DTM | / | / | / | 0.112 | 0.026 | *** | −0.081 | 0.027 | ** | −0.040 | 0.026 | . |
T_F_acc | −0.042 | 0.025 | . | −0.244 | 0.042 | *** | / | / | / | −0.223 | 0.040 | *** |
T_Curv_pl | −0.053 | 0.022 | ** | 0.100 | 0.025 | *** | −0.039 | 0.025 | . | −0.064 | 0.023 | ** |
T_Curv_st | 0.106 | 0.022 | *** | 0.146 | 0.024 | *** | −0.043 | 0.026 | . | −0.037 | 0.020 | . |
T_N | / | / | / | 0.054 | 0.025 | * | / | / | / | −0.112 | 0.024 | ** |
T_NE | / | / | / | −0.196 | 0.030 | *** | / | / | / | / | / | / |
T_E | / | / | / | −0.172 | 0.029 | *** | / | / | / | / | / | / |
T_SE | / | / | / | −0.040 | 0.025 | . | / | / | / | / | / | / |
T_S | 0.117 | 0.021 | *** | / | / | / | 0.061 | 0.025 | . | / | / | / |
T_SW | / | / | / | 0.038 | 0.023 | . | −0.052 | 0.025 | . | 0.060 | 0.021 | ** |
T_W | −0.038 | 0.023 | . | 0.141 | 0.027 | *** | −0.088 | 0.025 | *** | −0.043 | 0.024 | . |
T_NW | 0.067 | 0.022 | ** | / | / | / | / | / | / | 0.089 | 0.021 | . |
T_FLAT | −0.060 | 0.035 | . | −0.235 | 0.041 | *** | −0.089 | 0.034 | ** | / | / | / |
T_Ls | 0.182 | 0.024 | *** | 0.115 | 0.029 | *** | 0.175 | 0.027 | *** | 0.132 | 0.022 | *** |
T_TPI | 0.112 | 0.022 | *** | 0.060 | 0.022 | ** | 0.253 | 0.022 | *** | −0.036 | 0.021 | . |
S_Epic | 0.056 | 0.027 | * | −0.252 | 0.028 | *** | 0.286 | 0.031 | *** | −0.112 | 0.024 | * |
G_TA | −0.071 | 0.043 | . | −0.098 | 0.046 | * | −0.081 | 0.039 | * | −0.141 | 0.041 | *** |
G_SSC | 0.137 | 0.018 | *** | −0.113 | 0.024 | *** | 0.206 | 0.017 | *** | 0.030 | 0.020 | . |
G_CM | −0.042 | 0.022 | . | −0.132 | 0.025 | *** | −0.224 | 0.039 | *** | 0.034 | 0.019 | . |
G_C | −0.236 | 0.031 | *** | −0.333 | 0.040 | *** | −0.260 | 0.031 | *** | −0.319 | 0.035 | *** |
G_DDB | −0.262 | 0.037 | *** | −0.140 | 0.043 | *** | −0.244 | 0.038 | *** | −0.262 | 0.035 | *** |
G_LG | /0.134 | 0.044 | ** | −0.077 | 0.038 | * | −0.069 | 0.037 | . | −0.068 | 0.037 | . |
G_SC | 0.042 | 0.023 | . | 0.061 | 0.023 | ** | −0.280 | 0.033 | *** | / | / | / |
G_SSM | 0.045 | 0.019 | * | −0.136 | 0.034 | ** | −0.119 | 0.036 | ** | 0.101 | 0.010 | *** |
G_CCL | 0.099 | 0.022 | *** | −0.092 | 0.028 | ** | 0.083 | 0.023 | *** | 0.103 | 0.022 | * |
G_ML | / | / | / | 0.157 | 0.027 | ** | / | / | / | −0.077 | 0.024 | ** |
P_sand | −0.110 | 0.026 | *** | 0.095 | 0.028 | *** | −0.241 | 0.030 | *** | / | / | / |
P_silt | −0.169 | 0.023 | *** | −0.311 | 0.029 | *** | −0.161 | 0.024 | *** | 0.106 | 0.028 | *** |
LU_urb | 0.068 | 0.013 | *** | 0.130 | 0.011 | *** | −0.160 | 0.042 | *** | 0.066 | 0.013 | ** |
LU_grs | −0.072 | 0.024 | ** | −0.073 | 0.022 | *** | −0.257 | 0.037 | *** | −0.137 | 0.030 | ** |
LU_for | / | / | / | 0.079 | 0.023 | *** | −0.089 | 0.026 | *** | 0.148 | 0.021 | *** |
LU_nat | 0.149 | 0.016 | *** | 0.111 | 0.018 | *** | 0.064 | 0.017 | *** | / | / | / |
D_riv | −0.159 | 0.024 | *** | −0.041 | 0.022 | . | −0.213 | 0.031 | *** | 0.073 | 0.025 | ** |
D_road | −0.338 | 0.026 | ** | −0.389 | 0.028 | *** | −0.303 | 0.027 | *** | −0.380 | 0.028 | *** |
C_p_max | −0.039 | 0.023 | . | / | / | / | −0.164 | 0.025 | *** | 0.168 | 0.025 | *** |
Landslide | AIC * | AUC ** | Accuracy | McFadden’s Pseudo R2 |
---|---|---|---|---|
All | 8004.13 | 0.76 | 0.71 | 0.12 |
Rotational/Translational | 7407.88 | 0.68 | 0.73 | 0.19 |
Slow Earth Flow | 7200.94 | 0.80 | 0.77 | 0.21 |
Complex Landslide | 7828.44 | 0.69 | 0.70 | 0.13 |
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Ganga, A.; Elia, M.; D’Ambrosio, E.; Tripaldi, S.; Capra, G.F.; Gentile, F.; Sanesi, G. Assessing Landslide Susceptibility by Coupling Spatial Data Analysis and Logistic Model. Sustainability 2022, 14, 8426. https://doi.org/10.3390/su14148426
Ganga A, Elia M, D’Ambrosio E, Tripaldi S, Capra GF, Gentile F, Sanesi G. Assessing Landslide Susceptibility by Coupling Spatial Data Analysis and Logistic Model. Sustainability. 2022; 14(14):8426. https://doi.org/10.3390/su14148426
Chicago/Turabian StyleGanga, Antonio, Mario Elia, Ersilia D’Ambrosio, Simona Tripaldi, Gian Franco Capra, Francesco Gentile, and Giovanni Sanesi. 2022. "Assessing Landslide Susceptibility by Coupling Spatial Data Analysis and Logistic Model" Sustainability 14, no. 14: 8426. https://doi.org/10.3390/su14148426