*3.1. Overall Workflow*

The main objective of this paper is to use the data of various types of submarinelandslide-hazard impact factors as the basis for regional classification of submarine landslide hazards after data preprocessing and machine learning modeling. The study in this paper can provide an exploration of the hazard classification of global submarine landslides. The workflow of this study is shown in Figure 2, and includes the following specific steps:

• Data collection.

**Figure 2.** The general concept of the research method.

The data of this study are obtained from long-term geophysical surveys and in situ monitoring in the study area by the First Institution of Oceanography, MNR [20]. After data collection, we should determine suitable geological factors as submarine-landslideinfluencing parameters. Suitable impact parameters should be able to cover both the geological, hydrological, and human influential factors of landslides and be more readily available as common parameters.

• Influencing parameter determination.

After determining the factors influencing the submarine landslides, each data point was interpolated separately so that the values of all influencing factors were included at each study site in the study area. Subsequently, the data were classified into several categories according to the characteristics of different influencing factors, and the category distribution maps were drawn.

• Classification-level data extraction.

The coordinate values of the study-point locations are defined and the categories of each factor are extracted from the impact-factor classification map obtained in the previous step. The coordinate values of the study-point locations are defined and the categories of each factor are extracted from the impact-factor classification map obtained in the previous step. Thus, each study point corresponds to multiple classes of impact-factor parameters that can be used in the next step of unsupervised machine learning model training.

• Establishing unsupervised machine learning models.

Establish 3 unsupervised machine learning models using k-means, spectral clustering, and hierarchical clustering. The different parameters in the model are first modeled several times, and subsequently, the model parameter with the best prediction is selected to build the final established model.

• Accuracy comparison.

Compare the accuracy and rationality of different predicting results and choose the best one. Both the mathematical test metrics and the measured geological conditions should be used to test the models' accuracy. The Calinski–Harabasz index, silhouette index, and Davies–Bouldin index are used to calculate the mathematical accuracies. The liquefication zonation is used to calculate the geological rationality.

• Influencing parameter analysis.

Study the importance of all the landslide-influencing parameters by excluding them individually using the best model and test the accuracies with evaluating indicators.

#### *3.2. Landslide-Influencing Parameters*

It is very important to choose the suitable influencing factors for submarine landslide assessment. There is no absolute standard parameter when classifying the hazards of submarine landslides. This issue remains one of the difficult problems in the field of research on submarine landslides. The reason is that there are too many influencing factors and it is difficult to obtain the corresponding parameters. From the point of view of geological analysis, geological factors, hydrodynamic factors, topographic factors, and human activities should be taken into account. As much information as possible should be collected to satisfy these four requirements.

In this study, we have selected carefully out of all the various choices available based on the nature of submarine landslide occurrences concerning the characteristics of geology, hydrology, geomorphology, and the impact of human engineering activities. Therefore, 9 factors were selected, namely, sediment type, slope, soil strength, water depth, wave height, maximum current velocity of the bottom, liquefaction, erosion, and human engineering activities (Figure 3). The research data of the 9 factors were obtained by the First Institute of Oceanography, MNR, China through geophysical sounding, drilling, and monitoring surveys in the Chengdao sea area of the Yellow River Estuary [18], and contain detailed information on various geological features of the study area. Each factor was divided into 3 or 4 classes based on the range of data, geological background, and experts' experience in this study area. At last, 1107 points, of which longitudes vary from 118.75◦ N to 118.95◦ N, latitudes change from 38.15◦ N to 38.28◦ N, and 0.05 degrees is the interval, were selected as the research sites (Figure 1). All the data used in this study were collected from projects of the First Institute of Oceanography, MNR.

**Figure 3.** Location map of the study area. (**a**) Sediment type; (**b**) slope angle; (**c**) soil strength; (**d**) water depth; (**e**) wave height; (**f**) current velocity; (**g**) liquefaction; (**h**) erosion; (**i**) human engineering activities; (**j**) overlay map.

Sediment type plays an important role in the study of submarine landslide susceptibility, as different types of sediments have different physical and mechanical properties, which can affect the difficulty of geological disasters. Studies have shown that sediment type has a large influence on landslide stability [21]. In this study area, sediments are divided into 4 classes: silty sand, silt, silty clay, and clay.

Slope angle is a significant factor in the development of submarine landslide susceptibility and the angles were calculated by the change in water depth. Slope angles are subdivided into 4 categories: <1/2000 radian, 1/2000–1/1000 radian, 1/1000–1/500 radian, and >1/500 radian. The places with large sea-bottom slopes are mainly located at 6 m and 10 m water-depth contours.

Soil strength affects the stability and sliding difficulty of the submarine landslide. The greater the soil strength, the harder the slide occurs. Soil strength is divided into 0–50 kPa, 50–80 kPa, 80–110 kPa, and >110 kPa. The classification of soil strength is mainly based on data from boreholes in this study area.

Water depth, which was obtained by single-beam and multibeam bathymetric instruments, can influence the strength of waves acting on the seabed. It can be classified into 4 classes: 0–5 m, 5–10 m, 10–15 m, and >15 m.

Wave height is a very important factor because it represents the energy that a wave contains. It was collected by pressure wave and tide gauges. The wave height increases first with the depth of water, but there is no obvious increase after reaching a 9 m depth. The study area can be divided into 3 classes, which are 0.5–2.5 m, 2.5–4 m, and >4 m.

The maximum current velocity of the bottom determines the shear stress of the current on the seabed, which may cause erosion. Current velocity increases as the water depth increases and can be classified into 3 classes: 0–0.5 m/s, 0.5–1 m/s, and 1–1.5 m/s.

Liquefaction is the most serious geological hazard in the Yellow River Estuary. There are hundreds of liquefaction zones in the study area, which were discovered by geophysical explorations. Liquefaction zones are mainly distributed between a 6 m to 12 m water depth, where the strength of hydrodynamic action is the strongest. Liquefaction is divided into 4 classes: not easy to liquefy (liquefaction depth < 0.5 m), slightly liquefy (0.5 m < liquefaction depth<2m), moderate liquefy (2 m < liquefaction depth < 4 m), and serious liquefy (liquefaction depth > 4 m). Seabed sediments are easy to slide after liquefaction as their bearing capacity reduces greatly.

Erosion is divided into 4 classes, which are the stable zone (<0.02 m/s), slight zone (0.02–0.05 m/s), moderate zone (0.05–0.1 m/s), and serious zone (0.1 m/s). The serious zone and moderate zone are mainly distributed in a water depth of less than 12 m.

Human engineering activities are mainly offshore production platforms, submarine pipelines, cables, and so on in this study area. They can be divided into 4 categories: core zone, buffer zone, potential-impact zone, and no-impact zone. The actual scope of various engineering structures is named the core zone. The buffer zone is the core area extending 500 m outwards. The potential-impact zone is where the buffer zone extends another kilometer outward, and other areas are the no-impact zones.
