Observations of vegetation phenology provide valuable information regarding ecosystem response to environmental conditions,especially to climate change.Cotton is one of the most important economic crops in Xinjiang,and its phenological change can directly reflect the change of climate in Xinjiang.This research was an attempt to extract cotton phenological parameters in Xinjiang by using 16 years'(2001 to 2016)time series MODIS Normalized Difference Vegetation Index(NDVI):firstly,filtering noise from the time-series data using Savitzky-Golay filtered method;then detecting cotton phenology parameters(Start of Growth Season(SOS),End of Growth Season(EOS),Long of Growth Season(LOS))using Dynamic Threshold method;finally,the spatial patterns and temporal trends of observed cotton phenological characteristics were analyzed over the past 16 years and the relationship between cotton phenology and temperature changes was also discussed.The result of this study showed that the spatial patterns of cotton phenology were significantly different in study region:SOS delayed gradually from Nanjiang to Beijiang,and mainly occurred before 151 st and after 151 st days respectively;EOS gradually advanced,most areas of northern Xinjiang ended up 292 nd days ago,while the southern Xinjiang happened 298 th days later;LOS shortened,Nanjiang is generally longer than 150 days while Beijiang is usually shorter than 150 days.The trend of cotton phenology(2001~2016)under climate change in northern and southern Xinjiang were not completely similar: SOS and EOS in southern Xinjiang showed a delay-advancing-delay-advancing trend,and LOS was unsignificantly delayed;While SOS in northern Xinjiang were slightly advanced and EOS exhibited a delay trend followed by an advancing,LOS showed a shorten-lengthen-shorten trend.In addition,cotton phenology showed a strong correlation with the temperature:SOS and EOS were positively correlated with the beginning date of 15℃and the end date of 10℃respectively;SOS was negatively correlated with the spring temperature,while EOS had a positive correlation with autumn temperature.