Identification and assessment of the factors driving vegetation degradation/regeneration in drylands using synthetic high spatiotemporal remote sensing Data-A case study in Zhenglanqi, Inner Mongolia, China

Vegetation degradation is a direct distinguishing feature of land degradation in drylands and seriously affects the ecological balance and sustainable development of drylands. Existing assessment methods of vegetation degradation at the regional scale based on long-time-series data have many shortcomings, including coarse resolution and a diversity of vegetation indicators that are typically complex. In the present study, net primary productivity (NPP) was selected as a primary vegetation indicator. Taking Zhenglanqi in the Inner Mongolia Autonomous Region as the study area, a technical process for the assessment of vegetation degradation/regeneration and analysis of the associated driving forces was proposed at a medium-high resolution scale. First, integrating the high spatial resolution advantage of Landsat data and the high temporal resolution advantage of moderate resolution imaging spectroradiometer (MODIS) data, a time series annual NPP dataset from 2001 to 2016 at 30 m resolution was constructed by applying the spatial and temporal adaptive reflectance fusion model (STARFM) and improved Carnegie-Ames-Stanford Approach (CASA) model. Then, the areas of vegetation degradation and regeneration from 2001 to 2016 were identified and determined by annual NPP trend analysis using the Sen + Mann-Kendall method. Overall, vegetation in Zhenglanqi was generally characterized by regeneration, with the degraded and recovered areas being 0.8% and 11.4%, respectively. Nearly 20% of the areas covered by sandy land showed a significant trend of vegetation regeneration, which indicated that the sand-drifting control measures introduced in the Otindag sandy land and its surroundings had achieved significant results. Next, the driving forces of vegetation degradation and regeneration in Zhenglanqi were distinguished over the past 16 years through proposed multiple and partial regression methods. Human activities were the main driver of vegetation degradation and regeneration (68.6% for degradation, 59.9% for regeneration), and the combination of human activities and climate variation also played an important role in vegetation degradation and regeneration (29.3% for degradation, 39.4% for regeneration), which indicated that the significant improvement of vegetation was related to the implemented eco-restoration projects, and visually proved by comparison of high resolution satellite images taking in different years. This research is expected to provide technical support and scientific reference data for ecological protection and land management in the study area, as well as the development of ecological engineering strategies in the drylands of northern China.