A Fast Connection Method for Disconnected Coherent Points in Time-Series InSAR Processing

Time-Series Interferometric Synthetic Aperture Radar (TS-InSAR) has been extensively applied to ground deformation monitoring and disaster risk assessment. In this process, coherent point (CP) selection and connection are two essential steps. Typically, CPs are initially connected using methods such as Delaunay triangulation, followed by the estimation of deformation parameters for each edge. However, the removal of low-quality edges often fragments the initial network into multiple sub-networks, and reliable deformation estimation requires reconnecting these sub-networks into a single, fully connected network. Despite its importance, this problem remains challenging and has not been fully addressed. In this paper, we propose an efficient sub-network connection method, termed KDIE, which integrates a KD-tree–based distance searching strategy with an iterative expansion scheme. KDIE efficiently identifies connection edges using the KD-tree and progressively extends the search distance (SD) up to the atmospheric correlation distance (ACD), thereby avoids missing any connectable sub-networks and preferentially connects nearly all sub-networks with short edges. Compared with the existing multi-layer sub-network connection (MLSC) method, two experiments concerning C-band Sentinel-1A images over a mountainous landscape and X-band TerraSAR-X images over an urban area demonstrate that KDIE connects 1.84% and 0.25% more CPs than the MLSC method, while reducing computational time to only 5–8% of that required by the MLSC method.