Analysis of the recent trends in vegetation dynamics and its relationship with climatological factors using remote sensing data for Caspian Sea watersheds in Iran

. This study used NDVI, ET, and LST satellite images collected by moderate resolution imaging spectroradiom-eter 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 cor-relation between NDVI and ET, and also LST (R = 0.46 and 0.55, p-value = 0.05, respectively). In this season, the impact of pre-cipitation 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 correla-tion 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 sea-son, the main factor that controls vegetation coverage is LST. In the summer season, when precipitation is much higher than aver-age, 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.