Tourism, a key driver of regional economies and perceived “green industry,” faces challenges from irrational resource allocation and spatial overlaps, undermining sustainability. This study examines 825 tourism resources in China’s Hulunbuir Grassland, analyzing spatiotemporal patterns, influencing factors, and ecological impacts using GPP and NDVI data. Three development phases emerged: essential development, rapid growth, and upgrading. They present a spatial pattern with Hailar and Chen Barag as the center, and multiple other points, mainly affected by ethnic minority population proportions, tourist reception, tourist attraction density, and river networks. Ecological analysis reveals that tourism-induced disturbances cause less environmental stress than other human activities, with grassland NDVI in tourism areas improving during upgrading. However, the NDVI of grasslands under non-tourism disturbance is still superior to that of grasslands under tourism disturbance. The findings emphasize the need for optimized resource allocation and proactive monitoring of tourism’s ecological footprint to advance sustainable grassland tourism.

Grassland degradation (GD) varies markedly across space. Identifying potential drivers at the county level enables precise grassland conservation and supports a win–win between economic development and ecological protection. However, most existing studies adopt a single, region-wide lens and lack county-level analyses. Focusing on Ordos, we conduct a county-level assessment and rank potential driver groups using partial-order theory. The results indicated the following: (1) from 2000 to 2020, a total of 6.9% (6026 km²) of grassland was restored, while approximately 5.0% (4372 km²) underwent degradation, with grassland recovery outpacing degradation; (2) urbanisation and economic development were identified as the leading drivers in five counties, followed by human activities and climate (three), and livelihood development (one); and (3) Ordos should adopt county-level differentiated management strategies: controlling urban and industrial expansion in urbanisation and economic-development-dominated counties, regulating grazing and land-use activities in human-activity-dominated counties, implementing dynamic grazing bans and drought preparedness in climate-dominated counties, promoting livelihood diversification in livelihood-development-dominated counties, and applying priority-based integrated governance in multi-driver counties.