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Environmental Earth Sciences
Erschienen in: Environmental Earth Sciences 12/2019

01.06.2019 | Original Article

Long-term spatiotemporal variations in satellite-based soil moisture and vegetation indices over Iran

verfasst von: Elham Fakharizadehshirazi, Ali Akbar Sabziparvar, Sahar Sodoudi

Erschienen in: Environmental Earth Sciences | Ausgabe 12/2019

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Abstract

Soil moisture plays a crucial role in vegetation growth. However, the long-term influence of soil moisture on vegetation growth was not sufficiently understood in many regions, especially in developing countries, due to the lack of ground measurements. Remote sensing data provide a promising way to overcome this limitation. In this study, a long-term spatiotemporal variation in remote sensing surface soil moisture (SSM) and vegetation indices (VIs) and their relationship during 1988–2015 were analyzed over Iran. Trend-free pre-whitening Mann–Kendall test was applied for the detection of the trends in soil moisture and VIs time series. Also, the validity of the “dry gets drier, wet gets wetter” (DGDWGW) paradigm was examined throughout the country. Finally, the consistency between SSM and vegetation indices trends was investigated using homogeneity Chi-squared test. The results showed that the monthly average of the SSM over 45% of Iran is lower than 0.15 m3/m3. Seasonal average of SSM is 0.17 and 0.12 m3/m3 in spring and winter, respectively. On average, monthly SSM trends are downward in 70% of Iran, which 30% of those is statistically significant. Over the past 28 years, about 50% and 35% of Iran got drier with rates of 0.24 × 10−2 (spring) and 0.78 × 10−3 (summer) m3/m3 per year. According to DGDWGW paradigm examining, 14% of Iran follows the DGDWGW paradigm. Summer and spring normalized difference vegetation index (NDVI) and enhanced vegetation index values are less than 0.1 in about 45% and 65% of the areas, respectively. The NDVI values are decreased in 40% of Iran in the last 28 years, of which half of those are statistically significant. SSM trends were consistent with vegetation indices using a homogeneity test. About 45% of SSM trends agree in sign with NDVI values. Life zone in the Southeast of Iran is arid desert scrubs, and in this area with sparse vegetation cover, mixing the spectral of soil and vegetation causes a serious problem in vegetation indices representing therefore the prominent mismatch between SSM and vegetation indices trends which were observed in Southeast of Iran.
Nächster Artikel Ten-year prediction of groundwater level in Karaj plain (Iran) using MODFLOW2005-NWT in MATLAB

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Metadaten
Titel
Long-term spatiotemporal variations in satellite-based soil moisture and vegetation indices over Iran
verfasst von
Elham Fakharizadehshirazi
Ali Akbar Sabziparvar
Sahar Sodoudi
Publikationsdatum
01.06.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Environmental Earth Sciences / Ausgabe 12/2019
Print ISSN: 1866-6280
Elektronische ISSN: 1866-6299
DOI
https://doi.org/10.1007/s12665-019-8347-4

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