Ranking land degradation drivers in eastern Inner Mongolia using partial order theory and Hasse diagram analysis

Land degradation (LD) poses a major challenge to global sustainable development, with the attainment of land degradation neutrality recognised as a key indicator of Sustainable Development Goal 15.3 (SDG 15.3). This goal focuses on combating desertification, restoring degraded land and soil, and including land affected by desertification, drought, and floods, with the aim of creating a land degradation-neutral world by 2030. Eastern Inner Mongolia (EIM), a typical agro-pastoral transitional zone, has experienced increasingly severe LD in recent decades. Identifying its dominant drivers is essential for improving ecological governance and land use management capacity. This study employed the Global 30 m Land-Cover Dynamics Monitoring Product (GLC_FCS30D) to characterise the spatio-temporal patterns of LD across three periods: 1990-2000, 2000-2010, and 2010-2020. Twelve drivers were identified and categorised into four groups: natural, human activities, economic, and urbanisation. Using Partial Order Theory and the Hasse Diagram Technique, the influence intensity of each driver group was systematically evaluated and ranked for each period. The combination of POT and the HDT enables transparent, interpretable, and reproducible ranking of multiple drivers while accounting for nonlinear, hierarchical, and interdependent relationships, offering advantages over conventional statistical or machine learning methods. The results showed that: (1) from 1990 to 2020, approximately 23% of EIM experienced land cover change, with degradation rates of 0.78%, 0.36%, and 0.41% for the three periods, respectively, and restoration rates of 0.71%, 0.36%, and 0.29%, respectively, the net land degradation and restoration areas were 5.83 × 10⁴ km² and 4.62 × 10⁴ km², respectively; (2) the dominant drivers of LD were ranked and spatially distributed differently across each league and city; (3) In the first two periods, the order of influence was: urbanisation > natural > human activities > economic. In the third period, the order changed to: urbanisation > natural > economic > human activities. This study reveals the spatiotemporal dynamics and dominant drivers of LD in EIM, providing a scientific basis for formulating regional land management and ecological restoration policies. It also offers valuable references for optimizing land use strategies, curbing LD, and achieving the sustainable development goals.