Spatiotemporal Analysis of MODIS NDVI in the Semi-Arid Region of Kurdistan (Iran)

Mehdi Gholamnia,R. Khandan,S. Bonafoni,A. Sadeghi

Published 2019 in Remote Sensing

ABSTRACT

In this study, the spatiotemporal behavior of vegetation cover in the Kurdistan province of Iran was analyzed for the first time by TIMESAT and Breaks for Additive Season and Trend (BFAST) algorithms. They were applied on Normalized Vegetation Index (NDVI) time series from 2000 to 2016 derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The TIMESAT software package was used to estimate the seasonal parameters of NDVI and their relation to land covers. BFAST was applied for identifying abrupt changes (breakpoints) of NDVI and their magnitudes. The results from TIMESAT and BFAST were first reported separately, and then interpreted together. TMESAT outcomes showed that the lowest and highest amplitudes of NDVI during the whole time period happened in 2008 and 2010. The spatial distribution of the number of breakpoints showed different behaviors in the west and east of the study area, and the breakpoint frequency confirmed the extreme NDVI amplitudes in 2008 and 2010 found by TIMESAT. For the first time in Iran, a correlation analysis between accumulated precipitations and maximum NDVIs (from one to seven months before the NDVI maximum) was conducted. The results showed that precipitation one month before had a higher correlation with the maximum NDVIs in the region. Overall, the results describe the NDVI behavior in terms of greenness, lifetime, abrupt changes for the different land covers, and across the years, suggesting how the northwest and west of the study area can be more susceptible to drought conditions.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    Remote Sensing

  • Publication date

    2019-07-20

  • Fields of study

    Geology, Geography, Computer Science, Environmental Science

  • Identifiers
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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