# Monitoring and Analysis of Slope Geological Hazards Based on UAV Images
###### Abstract  
Slope-related geological disasters occur frequently in various countries, posing significant threats to surrounding infrastructure, ecosystems, and human lives and property. Traditional manual monitoring methods for slope hazards are inefficient and have limited coverage. To enhance the monitoring and analysis of geological hazards, a study was conducted on the legacy slopes of an abandoned quarry in Jinan, Shandong Province, China. High-resolution images of the slopes were captured using unmanned aerial vehicle (UAV) phase tilt photogrammetry, and three-dimensional models were subsequently constructed. Software tools, including LiDAR360 5.2 and ArcMap 10.8, were employed to extract slope geological information, identify disaster-prone areas, and conduct stability analyses. The Analytic Hierarchy Process (AHP) was employed to further evaluate the stability of hazardous slopes. The results reveal the presence of two geohazard-prone areas in the study area. Geological analysis shows that both areas exhibit instability, with a high susceptibility to small-scale rockfalls and landslides. The integration of UAV remote sensing technology with AHP represents a novel approach, and the combination of multiple analytical methods enhances the accuracy of slope stability assessments. U 20  
data acquisition based on years of practice, providing a theoretical foundation for solving UAV operational issues. [PERSON] et al. [11] focused on the Tianxi Expressway, the largest traffic hub, employing UAV technology to identify, measure, and analyze three types of high slopes. Their research provides intuitive, accurate, and timely data support for slope monitoring in the area. Their work plays a vital role in enhancing the accuracy and efficiency of land surveying and mapping, providing a scientific basis for land planning, resource management, and environmental protection. [PERSON] et al. [12] investigated the application of UAV-based photogrammetry for slope mapping and hazard assessment in three high-risk areas at Pahang Matriculation College, Malaysia, and highlighted slope angle analysis as a key criterion for landslide risk evaluation, offering actionable insights for infrastructure planning and disaster prevention. Slope stability monitoring is crucial for ensuring the safety of engineering projects and the smooth operation of various infrastructures, thereby maximizing their social and economic benefits [13; 14; 15; 16]. Traditional monitoring methods typically involve manually operated equipment such as levels, total stations, and GPS, which are inefficient, labor-intensive, and costly. Consequently, there is a growing consensus within the industry to seek faster and more efficient monitoring solutions for slopes [17; 18]. The \"sky-earth-time\" integrated slope investigation and monitoring system assesses the development characteristics and stability of unstable slopes in the survey area, providing a foundation for the targeted implementation of terrain restoration [19]. [PERSON] et al. [20] conducted extensive research on intelligent slope monitoring and proposed a monitoring model along with the key data processing elements. [PERSON] et al. [21] identified the key points for intelligently extracting slope features in the study area by investigating the characteristics of three-dimensional point-cloud images, thereby improving the processing of monitoring data. [PERSON] et al. [22] extracted orthophotos and digital surface models of the lagoon slope before and after the landslide using UAV images. They employed COSI-Corr software to calculate the offset information of characteristic points on the landslide surface and determined the vertical displacement, thereby analyzing the motion, material changes, and the formation and evolution processes of the landslide, as well as its damage mechanisms. [PERSON] et al. [23] provided an accurate real-time data processing solution for UAV mapping applications, which supports the widespread adoption and implementation of UAV mapping in practical applications.