Assessment of land surface vulnerability using time-series geospatial datasets

Abstract

Assessing land surface vulnerability is important for understanding ecosystem responses to environmental changes. However, quantitative studies are still lacking, particularly in capturing temporal dynamics. This study proposes a framework for quantitatively assessing land surface vulnerability by integrating time-series geospatial datasets from the “water-soil-climate-plant” system, which reflects the dynamics of surface water, soil erosion, drought, and vegetation. Based on dynamic data from these four subsystems during 1990−2022, the spatial heterogeneity of land surface vulnerability and its relationship with both natural and anthropogenic factors were analyzed in the Hohhot-Baotou-Ordos-Yulin urban agglomeration. The results indicate that a significant spatial overlap between areas of high land surface vulnerability and ecological management zones. Specifically, 6.1 % of severely vulnerable regions are concentrated in the Maowusu sandy land, the Kubuqi desert, and the Loess hilly-gully region. Severe vulnerability is also evident in the central part of the urban agglomeration, largely influenced by the compound effects of multiple subsystems. Among these subsystems, the proportion of regions with high and severe vulnerability is highest in drought (33.4 %), followed by soil (16.7 %), vegetation (9.9 %), and surface water (9.3 %). Human activities have facilitated ecosystem recovery in the Yinshan Daqing Mountains and parts of the Kubuqi desert, whereas restoration efforts in the Maowusu sandy land remains limited. In the Loess hilly-gully region, vulnerability intensifies with increasing human activity but is relatively less affected by aridity intensity. By integrating annual fluctuations from key land surface subsystems, this study offers a dynamic vulnerability assessment framework, providing valuable insights for enhancing land surface system resilience in response to ongoing climatic and anthropogenic challenges.

Keywords

• Vulnerability
• Complex systems
• Pixel scale
• Arid and semi-arid regions
• Hohhot-Baotou-Ordos-Yulin urban agglomeration