The uncertainty and variability of advancing wildfires present significant challenges to the resilience of power systems. This paper proposes a hierarchical dispatch strategy of multi-type virtual power plants (VPPs) for enhancing resilience of power systems under wildfires, which encompass geographically distributed VPPs (GDVPPs) based on Internet data centers (IDCs) and geographically concentrated VPPs (GCVPPs) that aggregate flexible loads (FLs). The proposed strategy enhances resistance to wildfire-induced uncertainties by facilitating coordinated operations between these two types of VPPs. At the upper level, an improved maximum flow model is introduced to quantify the dynamic changes in the workload transfer capability of IDC (WTCI) under wildfire conditions, and stochastic model predictive control (SMPC) is employed to perform rolling optimization of generator outputs, IDC workload transfers, and load shedding, thereby minimizing the total regulation costs. Based on the load shedding instructions from the upper level, the lower level integrates GCVPPs to provide load curtailment services, effectively offsetting the load shedding power. Subsequently, the lower level feeds back the load rebound (LR) resulting from these load curtailment services to the upper-level strategy, serving as a basis for its rolling optimization. The SMPC integrates an event-driven deductive model to address the fine-grained modeling of the operational state, effectively overcoming challenges posed by discrepancies in simulation time steps arising from power system cascading failures, variations in IDC adjustment capacity, and LR effects. Finally, a modified 39-bus power system, integrated with an 8-bus IDC network, is used as a case study to validate the effectiveness of the proposed strategy.