The annual spring river ice breakup has vast consequences for northern ecosystems as well as significant economic implications for Arctic industry and transportation. River ice breakup research is restricted by the sparse distribution of hydrological stations in the Arctic. A trend towards earlier ice breakup has been noted across the Arctic region, yet the specific climatic drivers of these trends are complex and can vary both regionally and within river systems. Consequently, understanding the response of river ice processes to a warming Arctic requires examination of both spatial and temporal trends in breakup timing. In this paper, I describe an automated algorithm for detecting the timing of river ice breakup using MODIS imagery that enables identification of spatial and temporal breakup patterns at whole-river scales and present an analysis of breakup timing on the Mackenzie, Lena, Ob and Yenisey rivers. Through splitting the rivers into 10 km segments and classifying each river pixel as snow, ice, mixed ice/water or open water, I am able to determine the dates of breakup from 2000-2014 with a mean uncertainty of around +/- 1.5 days. Where temporal trends are statistically significant, they are consistently negative, indicating an overall shift towards earlier breakup. Considerable variability in the statistical significance and magnitude of trends along each river suggests changing climatic drivers are impacting breakup patterns. Trends detected on the lower Mackenzie confirm previously observed weakening ice resistance and earlier breakup timing near the Mackenzie delta. In Siberia, the increased magnitude of trends upstream and strong correlation between breakup initiation and whole-river breakup patterns suggests that upstream discharge may play the dominant role in determining breakup timing. Exploratory analysis demonstrates that this method may in the future also be used to examine types of breakup events and assess event severity.