Assessment of the impacts of climate change and human activities on vegetation cover change in the Haihe River basin, China

Using the SPOT vegetation normalized difference vegetation index (NDVI) dataset from 2000 to 2013, we investigated the characteristics and future trends of spatiotemporal variations in vegetation in the Haihe River basin. At the same time, its associated driving factors were also analyzed. The Sen and Mann-Kendall models, the Hurst index and a partial correlation analysis were used to analyze the data. The study found that (1) the vegetation cover change of the study area exhibited a significant increase in 2000–2013 (linear tendency, 6.4%∕10 a). During 2002–2004, the vegetation growth rate was the fastest, while vegetation growth slowed after 2004. (2) Spatially, the vegetation coverage in the study area was good during the 14-year period but poor in the Bohai Bay area and in some urban centers. (3) The area of vegetation improvement in the Haihe River basin accounted for 90.35% of the total basin area, and the degraded area accounted for 5.90% of the area and was mainly distributed in the peripheral areas of some urban centers. (4) The change in vegetation coverage in the Haihe River basin towards sustainability was stronger and primarily exhibited a continuously increasing trend, accounting for 89.11% of the total area. (5) The change in vegetation coverage was mainly attributed to the increase in precipitation. (6) Human activities could induce dual effects on vegetation coverage, so they were also one of the most important factors affecting vegetation cover change. •We investigated the spatiotemporal variations characteristics in vegetation in the Haihe River basin from 2000 to 2013.•We analyzed the impacts of climate change and human activities on vegetation cover change.•NDVI showed that vegetation cover exhibited a significant increase in the study area during 2000–2013.•The change in vegetation coverage was mainly attributed to the increase in precipitation.•Human activities also had profound effect to the vegetation variation trends in the study area.