An Automatic Method to Detect Lake Ice Phenology Using MODIS Daily Temperature Imagery
An Automatic Method to Detect Lake Ice Phenology Using MODIS Daily Temperature Imagery
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DOI：
10.3390/rs13142711
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Xin Zhang;Kaicun Wang;G. Kirillin
中科院分区：
文献类型：
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作者：
Xin Zhang;Kaicun Wang;G. Kirillin
湖冰物候是一个气候敏感的指标。然而，地面监测受到人类视觉的限制，在恶劣环境中难以实施。遥感技术为探测湖冰物候提供了巨大的潜力。在这项研究中，开发了一种新的自动化方法来提取湖冰物候参数，通过捕获的过渡水/冰相的时间模式，使用参数化的时间函数。该方法基于中分辨率成像光谱仪（MODIS）每日温度产品，这些产品具有监测湖泊冰盖的独特潜力，因为从2002年到2016年，每天以1公里的空间分辨率提供四次观测。2002-2016年期间，选择了三个不同气候区域具有不同特征的季节性冰封湖泊进行测试。水/冰过渡阶段的时间模式的基础上，从MODIS每日温度数据提取的未冻水覆盖率，并与MODIS雪和反射率产品和Landsat图像进行了比较。一个很好的协议，R2的0.8以上的发现相比，中分辨率成像光谱仪的雪产品。提取的冰物候数据的年变化与MODIS反射率和AMSR-E/2产品具有较好的一致性。随后，该方法于2002年至2016年应用于中国北方9个季节性冰封湖泊。青藏高原湖泊中青海湖封冻开始日晚的趋势最强（6.31天/10年），呼伦湖封冻开始日和结束日迅速向早的方向移动（-3.73天/10年;-5.02天/10年）。该方法适用于估算和监测不同类型的湖泊在大尺度上的冰物候，并有很强的潜力，提供有价值的信息的冰过程对气候变化的响应。
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.