黄淮海平原是我国典型的农田生态系统之一,频发的低温冷害对该区域的冬小麦种植业造成了巨大的经济损失.为了有效、大范围地监测冷害的时空变化情况及其气象成因,利用2005–2015年来源于气象站点的逐日最低气温和MODIS的NDVI和FPAR数据,结合逻辑回归模型构建了黄淮海平原冬小麦低温冷害监测模型,并分析了2011–2020年黄淮海平原冬小麦冷害的时空变化.将其与气象要素的时空变化进行相关性分析,了解气象要素对冬小麦低温冷害发生情况的影响.结果表明,2011–2020年冬小麦冷害的危害性逐渐降低,且冷害发生高概率、高频区域由北向南移动.同时,气象要素对冬小麦受害程度的影响从高到低分别为热量、降水和日照时长,但这些要素的影响具有一定的空间异质性.“,”The Huang-Huai-Hai Plain is one of the typical agri-ecosystems in China, which suffers from cold dam-age frequently resulting in substantial economic losses. In order to monitor the changes in the occurrence of cold damage in an effective and large-scale manner, and to determine their meteorological causes, this paper collected low temperature data from the agricultural meteorological stations and remote sensing data of MODIS from 2005 to 2015, and constructed a monitoring model of cold damage to winter wheat in Huang-Huai-Hai Plain based on the Logistic regression model. This model was used to analyze the spatio-temporal changes of cold damage of winter wheat in Huang-Huai-Hai Plain from 2011 to 2020, and correlation analysis was performed with the spatio-temporal changes of meteorological factors to ascertain how they affect cold damage. The results show that the harm from cold damage in winter wheat has been gradually decreasing from 2011 to 2020, and the cold damage areas with high probability and high frequency are moving from north to south. The meteorological elements with the greatest impacts on the degree of cold damage from stronger to weaker are heat, precipitation and sunshine duration, whose influence has spatial variability.