The ecological conditions in the Inner Mongolia region are shaped by the interplay between natural processes and anthropogenic influences. As a vital ecological barrier in northern China, detailed monitoring of its vegetation dynamics is essential. This study pro-duced a 10-meter resolution vegetation map of Inner Mongolia for 2023 using the Random Forest classifier on the Google Earth Engine platform. We integrated Sentinel-2A/B imagery, spectral indices (band reflectance and spectral indices), topographic (elevation, slope, and aspect), and climatic data (annual precipitation and temperature) to classify vegetation into 14 types, with a key contribution being the subdivision of grassland into five distinct subtypes: meadow steppe (109660.1 km2), typical steppe (199455.2 km2), desert steppe (124556.5 km2), steppe-desert (109407.2 km2), and desert (144249.5 km2). This refinement addresses a significant gap in existing land cover products. The classification achieves an overall accuracy of 84.46%, with a Kappa coefficient of 0.83, demonstrating strong con-sistency with reference data and effectively capturing the vegetation distribution patterns in Inner Mongolia; Furthermore, among the 14 classified vegetation types, coniferous forest, broad-leaved forest, meadow steppe, typical steppe, desert steppe, steppe-desert, and desert display clear zonal distribution patterns, which are closely correlated with the region's climatic and topographic gradients. This study provides the latest high-resolution vegetation dataset and detailed area statistics for Inner Mongolia. The results provide critical data support for promoting sustainable development in Inner Mongolia and offer valuable insights into regional vegetation dynamics. (c) 2026 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.