The Mountain Excavation and City Construction project (MECC) in Yan'an New District (YND) on the Chinese Loess Plateau is one of the largest geotechnical works globally. Ground deformation resulting from these extensive earthworks continues to evolve spatially and temporally even after construction is completed. Monitoring this deformation is crucial for understanding uneven post-construction subsidence and ensuring the structural integrity of infrastructure. This study proposes a framework for monitoring and predicting postconstruction ground settlement (PCGS) using a dual-polarization Multi-temporal InSAR method (dual-pol MTInSAR) and Self-Attention Memory Convolutional Long Short-Term Memory (SAM-ConvLSTM) model. Compared to single-polarization (single-pol) MT-InSAR methods, the dual-pol MT-InSAR approach, which utilizes both polarization channels of Sentinel-1 (S1) SAR data, achieves a 24 % increase in Permanent Scatterer (PS) density for PS-InSAR and improves average coherence while reducing coherence standard deviation for Small Baseline Subset (SBAS). The study further examines the factors contributing to uneven ground deformation, including fill and excavation activities (e.g., the thickness and geotechnical properties of loess), construction activities and surface loads, and precipitation. A consolidation settlement model is employed to simulate and assess ground settlement decay due to loess compaction. Based on this analysis, the most affected area in Qiaoergou is selected for spatiotemporal forecasting using MT-InSAR measurements and the SAM-ConvLSTM model. The results indicate that regions with significant subsidence form a characteristic funnel shape, with subsidence increasing over time and the deformation perimeter expanding outward. The model achieved an average absolute error of 1.6 mm, with the majority of errors concentrated within 5 mm.