An Automated and Efficient Slope Unit Division Method Coupled with Computer Graphics and Hydrological Principles
Source abstract
Abstract
Slope units serve as fundamental spatial units for surface morphology modeling and multidisciplinary coupling analysis, holding significant theoretical value and practical implications in regional stability assessments, surface process simulations, and quantitative geological engineering research. The scientific delineation of slope units must simultaneously satisfy engineering implementation requirements and adhere to the unit homogeneity principle. However, conventional delineation like the hydrological process analysis method (HPAM) exhibits critical limitations, including strong threshold dependency, a low automation level, and single-attribute optimization, thereby restricting its applicability in complex scenarios. Based on the principles of unit consistency and hydrological processes, this study integrates computer graphics algorithms with hydrological process simulation techniques to propose an automated slope unit division method coupled with computer graphics and hydrological principles (SUD-CGHP). The method employs digital elevation model (DEM) input data to construct a three-stage hierarchical framework comprising (1) terrain skeleton extraction through a morphological erosion algorithm, (2) topological relationship iteration optimization, and (3) multisource parameter coupling constraints. This framework achieves automated slope unit delineation without thresholds while enabling multi-attribute fusion optimization, effectively addressing the shortcomings of HPAM. Field validation in Yanglousi Town, Hunan Province, demonstrates that SUD-CGHP-generated slope units exhibit superior internal homogeneity in flow direction, slope aspect, and gradient compared to HPAM while maintaining complete topographic–hydrological connectivity. The research findings indicate that this method significantly enhances the scientific validity and practical applicability of slope unit delineation, providing reliable spatial analysis units for multidisciplinary surface process modeling.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Landslides and related hazards · Soil and Unsaturated Flow · Geotechnical Engineering and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Geosciences and Info-Physics, Central South University, 932 Lushan South Road, Changsha 410083, China
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring (Central South University), Ministry of Education, 932 Lushan South Road, Changsha 410083, China
School of Civil Engineering, Yantai University, Yantai 264005, China
Hunan Province Geological Disaster Survey and Monitoring Institute, Changsha 410029, China
Geological Survey Institute of Hunan Province, Changsha 410083, China
Funding
National Natural Science Foundation of China · Natural Science Foundation of Hunan Province, China · Open Fund of Hunan Geological Disaster Monitoring, Early Warning and Emergency Rescue Engineering Technology Research Center
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