Decorrelation caused by temporal changes influences phase unwrapping of differential interferogram in repeat-pass D-InSAR phase delay due to atmosphere disturbance degrades the accuracy of D-InSAR for small deformation monitoring. In this paper, we present a stacking D-InSAR approach using multi-baseline differential interferograms to estimate the linear deformation based on Rank Defect Free Network Adjustment Model (RDFNA) and to increase the deformation temporal sampling rate and estimate the linear deformation accurately. The Minimum Cost Flow (MCF) algorithm based on Delaunay triangulation network generated with sparse grids is adapted for phase unwrapping of individual interferogram. Scatterers with high coherence values over a given threshold in the interferogram stack are selected for the network generation. Therefore, with the multi-baseline differential interferogram stack, the linear deformation rate can be calculated with the unwrapped phase of each point accurately.
Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on; 09/2006