# A New Parameter-Free Slope Unit Division Method That Integrates Terrain Factors
## 2 Methods and Study Area
### Principle of the Method  
In this paper, a DEM-based slope unit division scheme aimed at accurately dividing the surface into contiguous areas with similar slope, aspect, and curvature characteristics is proposed. This method achieves slope unit division on the basis of the principle of minimum regional heterogeneity. Unlike traditional hydrology-based subdivision methods, this approach relies more on terrain geometry to reflect natural slope variations more accurately. By combining a region-growing algorithm, starting from DEM grid pixels, it recursively expanded the neighborhood through region growing. This process assigned adjacent pixels with the same slope, aspect, and curvature categories into the same slope unit. Thus, it divided the entire study area into continuous, uniform, enclosed regions.  
The region-growing algorithm [32; 33] was first proposed by [PERSON] and [PERSON]. Its basic theoretical framework lies in dividing an image by identifying and aggregating pixel units with similar properties. The algorithm requires one or more seed points to be specified as starting points. It then traverses the neighboring pixels of the seed points and compares them with the seed points, incorporating the pixels that exhibit high similarity among predetermined attributes into the current growing region. This process continues in the outward direction until no accessible pixels meet the established similarity criteria, thus completing region growth.  
In this study, we used a dynamic seed-point selection mechanism. We adopted a pixel-by-pixel traversal method to identify and select unclassified pixels, also known as seed points, as the starting points for region growth. Therefore, every unassigned pixel has the potential to become a new seed point. This dynamic seed-point selection mechanism was implicitly implemented during the traversal process. A stacked structure was used to recursively label the eligible pixels and indicate that they are part of the same slope unit until all the eligible adjacent pixels were assigned, thus completing the slope unit division process. By dynamically selecting seed points and expanding neighborhoods based on terrain similarity, the slope unit subdivision becomes more flexible and detailed. This approach, combined with a recursive marking method using a stack structure, ensures unit continuity and completeness. This approach avoids both over-segmentation and under-segmentation in complex terrains. Ultimately, the entire study area was divided into relatively uniform slope units, each exhibiting high internal consistency in terms of slope, aspect, and curvature, providing a solid foundation for further geological and terrain analysis.  
By fully taking into account the influence of terrain factors and incorporating a dynamic seed-point selection mechanism, this subdivision method demonstrates strong adaptability in handling complex terrains, especially in scenarios requiring a fine-grained analysis of topographic features. The slope units generated by this method more accurately reflect natural slope forms, eliminating the artificial transition zones and irregular units commonly seen in traditional methods, offering a more natural and authentic terrain unit subdivision solution.