TY - JOUR
T1 - Analysis of the recent trends in vegetation dynamics and its relationship with climatological factors using remote sensing data for Caspian Sea watersheds in Iran
AU - Rousta, Iman
AU - Mansourmoghaddam, Mohammad
AU - Olafsson, Haraldur
AU - Krzyszczak, Jaromir
AU - Baranowski, Piotr
AU - Zhang, Hao
AU - Tkaczyk, Przemysław
N1 - Publisher Copyright:
© 2022 Institute of Agrophysics, Polish Academy of Sciences.
PY - 2022
Y1 - 2022
N2 - This study used NDVI, ET, and LST satellite images collected by moderate resolution imaging spectroradiometer and tropical rainfall measuring mission sensors to investigate seasonal and yearly vegetation dynamics, and also the influence of climatological factors on it, in the area of the Caspian Sea Watersheds for 2001-2019. The relationships have been assessed using regression analysis and by calculating the anomalies. The results showed that in the winter there is a positive significant correlation between NDVI and ET, and also LST (R = 0.46 and 0.55, p-value = 0.05, respectively). In this season, the impact of precipitation on vegetation coverage should not be significant when LST is low, as was observed in the analysed case. In spring, the correlation between NDVI and ET and precipitation is positive and significant (R = 0.86 and 0.55, p-value = 0.05). In this season, the main factor controlling vegetation dynamics is precipitation, and LST's impact on vegetation coverage may be omitted when precipitation is much higher than usual. In the summer, the correlation between NDVI and ET is positive and significant (R = 0.70, p-value = 0.05), while the correlation between NDVI and LST is negative and significant (R = -0.45, p-value = 0.05). In this season, the main factor that controls vegetation coverage is LST. In the summer season, when precipitation is much higher than average, the impact of LST on vegetation growth is more pronounced. Also, higher than usual precipitation in the autumn is the reason for extended vegetation coverage in this season, which is mainly due to increased soil moisture.
AB - This study used NDVI, ET, and LST satellite images collected by moderate resolution imaging spectroradiometer and tropical rainfall measuring mission sensors to investigate seasonal and yearly vegetation dynamics, and also the influence of climatological factors on it, in the area of the Caspian Sea Watersheds for 2001-2019. The relationships have been assessed using regression analysis and by calculating the anomalies. The results showed that in the winter there is a positive significant correlation between NDVI and ET, and also LST (R = 0.46 and 0.55, p-value = 0.05, respectively). In this season, the impact of precipitation on vegetation coverage should not be significant when LST is low, as was observed in the analysed case. In spring, the correlation between NDVI and ET and precipitation is positive and significant (R = 0.86 and 0.55, p-value = 0.05). In this season, the main factor controlling vegetation dynamics is precipitation, and LST's impact on vegetation coverage may be omitted when precipitation is much higher than usual. In the summer, the correlation between NDVI and ET is positive and significant (R = 0.70, p-value = 0.05), while the correlation between NDVI and LST is negative and significant (R = -0.45, p-value = 0.05). In this season, the main factor that controls vegetation coverage is LST. In the summer season, when precipitation is much higher than average, the impact of LST on vegetation growth is more pronounced. Also, higher than usual precipitation in the autumn is the reason for extended vegetation coverage in this season, which is mainly due to increased soil moisture.
KW - Caspian Sea watersheds
KW - evapotranspiration
KW - land surface temperature
KW - normalized difference vegetation index
KW - tropical rainfall measuring mission
UR - http://www.scopus.com/inward/record.url?scp=85133459933&partnerID=8YFLogxK
U2 - 10.31545/intagr/150020
DO - 10.31545/intagr/150020
M3 - Article
AN - SCOPUS:85133459933
SN - 0236-8722
VL - 36
SP - 139
EP - 153
JO - International Agrophysics
JF - International Agrophysics
IS - 3
ER -