RETRACTED ARTICLE: Prediction of mountain landslide susceptibility and influencing factors of green landscape design on both sides of roads

Abstract

By collecting basic data about the geological environment of the study area, this article introduces the geological environment of the study area in mountainous areas. Use data model, logistic regression model, and spatial logistic regression model to estimate the landslide susceptibility of the area and divide the research area. Based on the GIS platform and the regression model data model, seven evaluation factors were selected-altitude, rock characteristics, distance to the river, distance to the road, distance to the fault zone, vegetation and rainfall, etc. Using spatial logistic regression model and information model to carry out landslide risk prediction and regional assessment in this area, it shows that the development of mountain landslide disasters in the study area has considerable spatial effects. The areas with extremely high and high susceptibility to mountain landslides are mainly distributed in the study area. The southwest region is mainly distributed along rivers, both sides of roads, and near fault zones; most of the low- and medium-risk areas are scattered in higher altitude areas, with large slopes, low human activities, and high vegetation coverage. At the same time, the issue of green landscape setting on both sides of the highway is also mentioned. The green landscape system is composed of the highway itself and the attached green spaces on both sides. At present, many studies on the landscape system of the two roads are focused on improving the engineering technology of the main body of the highway and improving the landscape effect. The attached green space on both sides of the road is taken as the main focus of the research. The green space on both sides of the road is an important part of the ecological zone and plays an irreplaceable ecological role. Therefore, this paper conducts a more in-depth study on the use of disaster-prone prediction technology to study landslides and the current green landscape design on both sides of the road.