Forest ecosystems are crucial for global carbon sequestration and climate change mitigation. In Northeast India, evaluating forest biomass and carbon are essential because of the region’s high biodiversity and prevailing disturbances such as urbanization and shifting cultivation. This study aimed to estimate biomass, carbon stock, and sequestration potential along an altitudinal gradient in Kolasib district of Mizoram integrating field inventories with Sentinel-2 (S-2) data. A total of 0.6-hectare permanent sample plots were established at low-altitude (LAF) (< 500 m) and high-altitude (HAF) (> 500 m) forests. Field data were collected and species-wise volumetric equations were used to estimate the aboveground biomass, carbon stock, and sequestration for the time period of 2023–2024 and 2024–2025. Corresponding spectral vegetation indices were extracted from S-2 imagery using the Google Earth Engine (GEE). Multiple Linear Regression (MLR) and Random Forest (RF) model was applied to predict spatial biomass and carbon stock distribution. The field-based results showed that the low-altitude forest stores higher mean aboveground biomass (AGB) (456.08 t ha− 1) than the high-altitude forest (438.30 t ha− 1). The findings revealed that biomass was significantly (P < 0.0001) affected by tree diameter. While the MLR and RF models show mean AGB of 436 t ha− 1 and 475 t ha− 1, with corresponding aboveground carbon (AGC) of 113 t ha− 1 and 123 t ha− 1 respectively. Overall, the study area landscape demonstrated a substantial mean carbon stock of 264.83 t ha− 1 and an active carbon sequestration rate of 6.74 t ha− 1 yr− 1. This highlights the vital role of regional carbon sinks in mitigating climate change and supporting REDD+ initiatives.