## 4 Conclusions and Outlook
### Outlook  
Although the combination of the LKN-UKAN and FTTL has made significant progress in landslide segmentation, several challenges remain. The limited scale and diversity of the target dataset (Landslide-Expand) may have constrained generalization to unseen scenarios. Future research will focus on the following aspects: (1) investigating adaptive weight ratio adjustments for \(\alpha\) and \(\beta\) in the DLFFSKA module to further optimize feature fusion; (2) exploring more effective layer-freezing strategies in FTTL for different remote sensing image segmentation tasks; and (3) validating the applicability and generalizability of the LKN-UKAN in a wider range of remote sensing image processing tasks. Additionally, although the model reduced the parameters compared with U-Net++, its computational efficiency in real-time applications requires further validation. Lightweight adaptations, such as model pruning or adaptive layer compression, could optimize deployment on edge devices.  
To align with practical needs, future research should focus on the performance in specific landslide scenarios, such as small-area landslides and obstructed landslides, and explore integration with geographic information systems (GISs) for real-time hazard management. Finally, validating the LKN-UKAN's applicability to broader remote sensing tasks, such as single-type image segmentation or multi-class geological hazard detection, will strengthen its versatility. Addressing these challenges through interdisciplinary collaboration will bridge algorithmic innovation with real-world geological risk mitigation, ensuring the model's reliability and scalability in diverse operational scenarios.  
**Author Contributions:** Conceptualization, [PERSON] ([PERSON]), Q.L. and K.Z.; methodology, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and Q.X.; software, [PERSON] ([PERSON]), L.W. and Q.X.; validation, [PERSON] ([PERSON]), L.W. and Q.X.; formal analysis, [PERSON] ([PERSON]), Q.L., [PERSON] ([PERSON]) and K.Z.; investigation, [PERSON] ([PERSON]), [PERSON] ([PERSON]) and K.Z.; resources, [PERSON] ([PERSON]), Q.L. and K.Z.; data curation, [PERSON] ([PERSON]); writing--original draft preparation, [PERSON] ([PERSON]) and L.W.; writing--review and editing, [PERSON] ([PERSON]), Q.L., [PERSON] ([PERSON]), L.W. and K.Z.; visualization, [PERSON] ([PERSON]), L.W. and Q.X.; supervision, Q.L., [PERSON] ([PERSON]) and K.Z.; project administration, Q.L., [PERSON] ([PERSON]) and K.Z.; funding acquisition, Q.L. and [PERSON]. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the Science and Technology Project of Xiang Autonomous Region (XZ202501 YD0008), the Project of Southwest University of Science and Technology (21)IPKC13) and the National Natural Science Foundation of China (62362017).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.