Research on the temporal and spatial changes of vegetation coverage in Yulin based on GEE cloud platform

doi:10.14088/j.cnki.issn0439-8114.2022.16.012

Abstract

Abstract: Based on the Google earth engine （GEE） platform, the Landsat 5/7/8 image and pixel binary model are used to analyze the spatiotemporal changes of vegetation coverage in Yulin from 2000 to 2019 and its relationship with topographical factors and climate factors. Finally, the Hurst index is used to forecast the vegetation change trend of Yulin in the future. The results showed that the vegetation coverage of Yulin increased from northwest to southeast from 2000 to 2019, with the middle vegetation coverage area accounting for the largest proportion; during the study period, the vegetation coverage increased by 11.2%, and the growth rate was 1.37%; the area with improved vegetation coverage accounted for 63.0%, and the degraded area accounted for 27.9%. The influence of topography and climate change on vegetation is as followsvegetation coverage first rises and then declines with the increase in elevation, and rises with the increase in slope. Precipitation has a greater impact on vegetation coverage, followed by temperature; the average Hurst index is 0.58. In the future, the vegetation coverage of Yulin will be improved continuously. Research shows that since the implementation of the project of returning forests and grasses in Yulin, the overall vegetation coverage has been improved. The control effect of the hilly and gully areas in the south is better than that of the sandy areas in the north. In the post-reforesting cultivated land era, researchers should focus on ecological construction projects such as sand prevention and control as well as water and soil conservation in sandstorm areas.

Key words: vegetation coverage, Google earth engine, temporal and spatial changes, Yulin City

CLC Number:

X87
Q948

BAI Xin, HE Bing-yan, GAO Ting, LI Xue, SUN Qiao. Research on the temporal and spatial changes of vegetation coverage in Yulin based on GEE cloud platform[J]. HUBEI AGRICULTURAL SCIENCES, 2022, 61(16): 70-75.

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