Vegetation Change Detection Using Trend Analysis and Remote Sensing
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.
- Coppin P, Jonckheere I, Nackaerts K, Muys B, Lambin E (2004) Digital change detection methods in ecosystem monitoring: a review. International of thematic mapper data—the TM tasselled cap. IEEE Trans Geosci Remote Sens 25:1565–1596Google Scholar
- Kendall MG (1975) Rank correlation methods. Griffin, London, UKGoogle Scholar
- Li Z, Chen Y, Li W, Deng H, Fang G (2015) Potential impacts of climate change on vegetation dynamics in Central Asia. J Geophys Res: Atmos 120:2045–2057Google Scholar