# Landslide Susceptibility Mapping Based on Information-GRUResNet Model in the Changzhou Town, China

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## Abstract

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## 1. Introduction

## 2. Materials and Methods

#### 2.1. Study Area

^{2}. Changzhou town is located at the confluence of the Xunjiang and Guijiang Rivers, which form the Xijiang River after their confluence. This river traverses urban areas from west to east, and the Xunjiang, Guijiang, and Xijiang Rivers meet the Wuzhou. The terrain features are high on all sides and low in the middle, with hills accounting for more than 80% of the total area. There are many rolling hills and continuous mountains, with little flat land. The terrain slopes from north to south to the central Xijiang River and mainly consists of hills and platforms below 300 m above sea level. The Tropic of Cancer passes through Changzhou town. The area has a subtropical humid monsoon climate featuring strong solar radiation, abundant sunshine, warm temperatures, abundant rainfall, a short winter, and a long frost-free period. The average annual rainfall totals 1503.6 mm. The specific geographical location of Changzhou town is shown in Figure 1.

#### 2.2. Environmental Factors

#### 2.3. Process of Regional Landslide Susceptibility Mapping Based on the Information-GRUResNet Model

#### 2.4. Normalization

#### 2.5. Principal Component Analysis

#### 2.6. Information Theory

#### 2.7. GRU Model

#### 2.8. ResNetGRU Model

#### 2.9. Evaluation Index

## 3. Results

#### 3.1. Landslide Susceptibility Mapping Based on Information Theory

#### 3.2. Landslide Susceptibility Mapping with the Information-GRUResNet Model

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 4.**Process of regional landslide susceptibility mapping based on the Information-GRUResNet model.

**Figure 10.**Comparison of the landslide susceptibility mapping results of Information-GRUResNet and the GRU, RF, and LR models.

**Figure 11.**Comparison of the ROC and AUC results for the Information-GRUResNet, GRU, RF, and LR models.

**Figure 12.**Comparison of the ROC and AUC results for the Information-GRUResNet, GRU, RF, and LR models.

Landform | Geological Structure | Lithological Class | Human Activity Level | Slope Type | Regional Slope |
---|---|---|---|---|---|

47.43% | 12.76% | 9.36% | 9.85% | 12.2% | 8.4% |

Environmental Factors | Number of Landslide Points | Total Number of Landslide Points | Number of Grids for Each Factor | Grid Area of Each Factor | Total Grid Area | Information Theory Value | Normalized Information Theory Value |
---|---|---|---|---|---|---|---|

Landform | |||||||

High hills | 8 | 65 | 200,519 | 180,467,100 | 309,358,800 | −1.55599245 | 0.073032586 |

Low mountains and shallow-cut terrain | 47 | 65 | 43,898 | 39,508,200 | 309,358,800 | 1.733753855 | 1 |

Undulating mounds | 8 | 65 | 34,353 | 30,917,700 | 309,358,800 | 0.208227205 | 0.570145123 |

Valley terraces | 2 | 65 | 64,962 | 58,465,800 | 309,358,800 | −1.81518028 | 0 |

Geological structure | |||||||

>500 | 50 | 65 | 243,989 | 219,590,100 | 309,358,800 | 0.080374877 | 0.729635056 |

250–500 | 4 | 65 | 48,020 | 43,218,000 | 309,358,800 | −0.81984821 | 0 |

100–250 | 5 | 65 | 30,749 | 27,674,100 | 309,358,800 | −0.15094454 | 0.542149574 |

<100 | 6 | 65 | 20,974 | 18,876,600 | 309,358,800 | 0.413950908 | 1 |

Lithological class | |||||||

Sandstone | 0 | 65 | 4903 | 4,412,700 | 309,358,800 | - | - |

Quaternary system | 7 | 65 | 76,970 | 69,273,000 | 309,358,800 | −0.73203057 | 0 |

Clastic rock | 51 | 65 | 225,559 | 203,003,100 | 309,358,800 | 0.178718881 | 1 |

Granite | 7 | 65 | 36,300 | 32,670,000 | 309,358,800 | 0.019567422 | 0.825252204 |

Human activity level | |||||||

Very weak | 1 | 65 | 86,154 | 77,535,600 | 309,358,800 | −2.79062268 | 0 |

Strong | 16 | 65 | 108,166 | 97,349,400 | 309,358,800 | −0.24560334 | 0.531037444 |

Moderate | 36 | 65 | 25,715 | 23,143,500 | 309,358,800 | 2.001919473 | 1 |

Weak | 12 | 65 | 123,697 | 111,327,300 | 309,358,800 | −0.66745336 | 0.443015263 |

Slope type | |||||||

Transverse slope | 26 | 65 | 108,546 | 97,691,400 | 309,358,800 | 0.236397506 | 0.705986485 |

Reverse slope | 6 | 65 | 38,431 | 34,587,900 | 309,358,800 | −0.19162994 | 0.347459581 |

Oblique slope | 15 | 65 | 80,151 | 72,135,900 | 309,358,800 | −0.01038714 | 0.499273258 |

Forward slope | 1 | 65 | 4397 | 3,957,300 | 309,358,800 | 0.184552524 | 0.662559782 |

Soil layer thickness <2 m | 5 | 65 | 48,490 | 43,641,000 | 309,358,800 | −0.60644466 | 0 |

Soil layer thickness 2–4 m | 6 | 65 | 44,161 | 39,744,900 | 309,358,800 | −0.33060756 | 0.231048318 |

Soil layer thickness 4–6 m | 0 | 65 | 1922 | 1,729,800 | 309,358,800 | - | - |

Soil layer thickness >6 m | 6 | 65 | 17,634 | 15,870,600 | 309,358,800 | 0.587405627 | 1 |

Regional slope | |||||||

<15 | 15 | 65 | 100,225 | 90,202,500 | 309,358,800 | −0.23389244 | 0.583159479 |

25–35 | 5 | 65 | 75,284 | 67,755,600 | 309,358,800 | −1.04635470 | 0 |

>=35 | 45 | 65 | 168,222 | 151,399,800 | 309,358,800 | 0.346852968 | 1 |

15–25 | 0 | 65 | 0 | 900 | 309,358,800 | - | - |

**Table 3.**The number of landslides corresponding to different susceptibility levels determined based on the information theory method.

Susceptibility Level | Number of Grids in the Region | Proportion of Grids (%) | Number of Landslides | Proportion of Landslides (%) |
---|---|---|---|---|

Very high | 74,118 | 21.56 | 39 | 60 |

High | 101,529 | 29.54 | 14 | 21.54 |

Moderate | 76,771 | 22.33 | 7 | 10.77 |

Low | 70,866 | 20.62 | 4 | 6.15 |

Very low | 20,448 | 5.95 | 1 | 1.54 |

**Table 4.**The number of landslides of different susceptibility levels estimated with the Information-GRUResNet model.

Susceptibility Level | Number of Grids in the Region | Proportion of Grids (%) | Number of Landslides | Proportion of Landslides (%) |
---|---|---|---|---|

Very high | 74,118 | 21.56 | 39 | 60 |

High | 101,529 | 29.54 | 14 | 21.54 |

Moderate | 76,771 | 22.33 | 7 | 10.77 |

Low | 70,866 | 20.62 | 4 | 6.15 |

Very low | 20,448 | 5.95 | 1 | 1.54 |

**Table 5.**Number of landslides in different susceptibility levels for the Information-GRUResNet, GRU, RF, and LR models.

Susceptibility Level | Information-GRUResNet | GRU | RF | LR |
---|---|---|---|---|

Very high | 39 | 13 | 24 | 15 |

High | 14 | 33 | 14 | 34 |

Moderate | 7 | 11 | 17 | 7 |

Low | 4 | 6 | 6 | 8 |

Very low | 1 | 2 | 0 | 1 |

Model | MSE | MAE | RMSE |
---|---|---|---|

Information-GRUResNet | 1.32307692 | 0.83076923 | 1.15025081 |

GRU | 1.67692308 | 1.01 | 1.29496065 |

RF | 2.13846154 | 1.09230769 | 1.46234795 |

LR | 1.89230769 | 1.03076923 | 1.37561175 |

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## Share and Cite

**MDPI and ACS Style**

Lin, Z.; Chen, Q.; Lu, W.; Ji, Y.; Liang, W.; Sun, X.
Landslide Susceptibility Mapping Based on Information-GRUResNet Model in the Changzhou Town, China. *Forests* **2023**, *14*, 499.
https://doi.org/10.3390/f14030499

**AMA Style**

Lin Z, Chen Q, Lu W, Ji Y, Liang W, Sun X.
Landslide Susceptibility Mapping Based on Information-GRUResNet Model in the Changzhou Town, China. *Forests*. 2023; 14(3):499.
https://doi.org/10.3390/f14030499

**Chicago/Turabian Style**

Lin, Zian, Qiuguang Chen, Weiping Lu, Yuanfa Ji, Weibin Liang, and Xiyan Sun.
2023. "Landslide Susceptibility Mapping Based on Information-GRUResNet Model in the Changzhou Town, China" *Forests* 14, no. 3: 499.
https://doi.org/10.3390/f14030499