## 4 Discussion  
The SOE framework introduced in this study represents a significant advancement in the identification and characterization of urban-rural fringes. By integrating multidimensional data sources, our approach addresses the limitations of traditional methods that often rely on single indicators or administrative boundaries. One of the key strengths of our methodology is its ability to capture the complex and heterogeneous nature of urban-rural fringes. The combination of remote sensing imagery, nightlight data, building footprints, and POI information provides a comprehensive view of these transitional zones, reflecting their physical, functional, and socioeconomic characteristics. This multi-faceted approach allows for a more nuanced understanding of the gradual transition from urban to rural landscapes, which is often overlooked in binary urban-rural classifications [55]. The validation of our results through multiple perspectives, including nightlight intensity, building attributes, POI distribution, human activity patterns, and landscape indicators (Figures 4-7, Table 1), demonstrates the robustness of the SOE framework. The consistent intermediate values observed across these metrics for the identified urban-rural fringe areas confirm their transitional nature and highlight the effectiveness of our method in capturing the unique characteristics of these zones. The intermediate values exhibited by urban-rural fringes across multiple dimensions have significant implications for urban planning. These transitional characteristics suggest that traditional binary urban-rural planning approaches may be inadequate for these areas. Instead, urban planners should consider mixed-use development strategies that acknowledge the coexistence of urban and rural functions. Furthermore, the stable population distribution patterns observed in urban-rural fringes, compared to the pronounced commuting flows in urban cores, indicate the need for distinctive infrastructure and transportation planning approaches. These areas also require careful consideration in terms of balancing urban service needs with environmental conservation, particularly given their role as ecological buffers between urban and rural zones. Such planning considerations, informed by our empirical findings, can help create more resilient and sustainable urban-rural transitions while preserving the unique characteristics that make these areas valuable to both urban and rural systems. Our findings can directly inform specific policy decisions; for instance, the high proportion of enterprises but lower density of public services revealed in our POI analysis could guide local governments in prioritizing public facility development in fringe zones. However, it is important to acknowledge certain limitations and areas for future research. While our study focused on Beijing, the applicability of the SOE framework to other \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Indicators** & **Urban** & **Fringe** & **Rural** \\ \hline Cropland\_\%LAND & 6.51\% & 25.70\% & 26.43\% \\ Forest\_\%LAND & 0.11\% & 1.16\% & 56.82\% \\ Grassland\_\%LAND & 0.01\% & 0.03\% & 3.07\% \\ Water\_\%LAND & 0.58\% & 0.88\% & 1.51\% \\ Impervious\_\%LAND & 92.79\% & 72.22\% & 12.17\% \\ SHDI & 0.41 & 0.98 & 1.59 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of landscape indicators for the three land types. urban contexts, particularly in different cultural and economic settings, needs further investigation. The transferability of this method to cities with varying urbanization patterns and data availability should be explored to establish its broader applicability. Additionally, the static nature of our analysis, based on data from a single year, does not capture the dynamic processes of urban expansion and rural transformation. Future studies could incorporate temporal analyses to track the evolution of urban-rural fringes over time, providing insights into the pace and patterns of urbanization.