Vegetation Change Detection Using Trend Analysis and Remote Sensing

  • Youjia LiangEmail author
  • Lijun Liu
  • Jiejun Huang
Part of the Springer Geography book series (SPRINGERGEOGR)


Vegetation change has become a worldwide environmental concern. We explored spatial and temporal patterns of vegetation change through examining time series Normalized Difference Vegetation Index (NDVI) over the period 1975–2010 in an artificial desert oasis in northwest China. A time series of remote sensing imagery derived from Landsat product was analyzed for the presence of trends in vegetation change, using the nonparametric Sen’s and Mann–Kendall methods. As a whole, over 13.56% of oasis land surfaces were found to exhibit significant increasing trends, and almost 6.07% of oasis land surfaces were found to exhibit significant decreasing trends. In addition, the 80.38% spatial distribution of vegetation showed no change trends significantly. The relationships between the detected NDVI trends and land cover also was evaluated based on quantitative methods. Results showed that the spatio-temporal pattern of vegetation change was consistent with the climate-related change of vegetation growing conditions and implementation of ecosystem management during the study period.


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© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Resources and Environmental EngineeringWuhan University of TechnologyWuhanChina
  2. 2.Department of NavigationWuhan University of TechnologyWuhanChina

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