Mangroves are critical for climate change adaptation but face increasing threats from hurricanes and anthropogenic pressures. Quantitative baselines for post-disturbance conditions remain limited in Cuba. We integrated field forest inventories (40 permanent 100 m² plots) with remote sensing time series (aerial photographs: 1957, 1970, 1999; Landsat 7: 2003; Sentinel-2A: 2022, 2025) in La Coloma, southwestern Pinar del Río, Cuba. Biophysical variables (diameter, height, basal area, ecological importance value index) and seven spectral indices (Normalized Difference Vegetation Index (NDVI), Mangrove Vegetation Index (MVI), Green Cover Index (GCI), Enhanced Vegetation Index-2 (EVI-2), Normalized Difference Salinity Index (NDSI), Normalized Difference Moisture Index (NDMI), Natural Regeneration Index (IRN)) were analyzed. Classification accuracy was assessed using confusion matrix and Kappa coefficient. The mangrove forest presents low-stature structure (mean height: 4.16 m; mean diameter at 1.30 m: 5.41 cm). Total basal area was 7.41 m²·ha⁻¹. Hurricane Ian (September 2022) affected 54% of individuals (351 trees). Mangrove cover increased from 6,434 ha (1957) to 7,282 ha (2022), a net increase of 848 ha (11.64%). Spectral indices revealed progressive degradation: MVI confirmed an alarming 161.8% increase (154.0 ha) in moderately degraded areas. Overall, 403.5 ha (33% of the total analyzed area) were degraded (199.4 ha highly degraded, 204.2 ha degraded), with 288.6 ha regenerating and 546.6 ha healthy. Classification accuracy was 87.3% (Kappa = 0.84). Six anthropogenic and three natural stressors were identified, including the defoliating lepidopteran Junonia genoveva affecting 80% of sampled areas. Integrating field inventories with Sentinel-2 remote sensing and GIS (Geographic Information System) enables precise post-disturbance mangrove diagnosis. The established baseline serves as a predictive tool for land-use planning and assisted restoration prioritization under Cuba's "Tarea Vida" climate adaptation plan.