Concluding Remarks

This book covers fundamental topics in remote sensing image change detection and computational intelligence. In previous chapters, we have reviewed core concepts of change detection and presented deep learning solutions for both homogeneous and heterogeneous scenarios. We have also explored emerging computational intelligence techniques such as neural architecture search to further improve change detection performance and enhance model autonomy. Despite these advances, many challenges remain unresolved. In this chapter, we outline promising future research directions from five perspectives, aiming to bridge the gap between current capabilities and real-world demands in complex, evolving, and resource-constrained environments.