In mountainous wildfire response, unmanned aerial vehicle (UAV) emergency services depend on rapidly deployable and spatially reliable vertiports. However, existing site-selection methods insufficiently support continuous UAV operations in topographically complex terrain. This study develops a geographic information system (GIS)-based framework integrating Multi-Criteria Decision-Making (MCDM) and k-medoids clustering to shift UAV vertiport planning from individual site suitability ranking to networked deployment. The framework organizes feasible vertiport candidates into sector-based support staging nodes for coordinated multi-node wildfire response. Applied to the Xichang wildfire, the selected vertiport candidates reduced the mean first-arrival time by up to 71.4% compared with existing fire stations. Under differentiated reload-time assumptions, the staging node support mode further reduced the mean sortie cycle time by up to 56.85% and increased the mean delivery capacity from 17 to 42 fire-extinguishing bombs per UAV per hour. These results indicate that combining vertiport suitability evaluation with staging node-based logistical coordination improves the spatial organization and operational efficiency of UAV-enabled wildfire suppression. The framework offers decision support for networked UAV vertiport and staging node deployment in mountainous wildfire response.