An Automatic Method to Detect Lake Ice Phenology Using MODIS Daily Temperature Imagery

Abstract

Lake ice phenology is a climate-sensitive indicator. However, ground-based monitoring suffers from the limitations of human vision and the difficulty of its implementation in harsh environments. Remote sensing provides great potential to detect lake ice phenology. In this study, a new automated method was developed to extract lake ice phenology parameters by capturing the temporal pattern of the transitional water/ice phase using a parameterized time function. The method is based on Moderate-Resolution Imaging Spectroradiometer (MODIS) daily temperature products, which have unique potential for monitoring lake ice cover as a result of providing four observations per day at 1 km spatial resolution from 2002 to 2016. Three seasonally ice-covered lakes with different characteristics in different climate regions were selected to test the method during the period of 2002–2016. The temporal pattern of water/ice transition phase was determined on the basis of unfrozen water cover fraction extracted from the MODIS daily temperature data, and was compared with the MODIS snow and reflectance products and Landsat images. A good agreement with an R2 of above 0.8 was found when compared with the MODIS snow product. The annual variation of extracted ice phenology dates showed good consistency with the MODIS reflectance and AMSR-E/2 products. The approach was then applied to nine seasonally ice-covered lakes in northern China from 2002 to 2016. The strongest tendency towards a later freeze-up start date was revealed in Lake Qinghai (6.31 days/10 yr) among the lakes in Tibetan plateau, and the break-up start and end dates rapidly shifted towards earlier dates in Lake Hulun (−3.73 days/10 yr; −5.02 days/10 yr). The method is suitable for estimating and monitoring ice phenology on different types of lakes over large scales and has a strong potential to provide valuable information on the responses of ice processes to climate change.