Abstract: The sub-surface waterlogging is a major agricultural meteorological disaster that affects the yield of summer crops in the middle and lower basins of the Yangtze River, Waterlogging disaster has the characteristics of concealment and hysteresis. At present, there is a little research on the extraction of crop waterlogging spatial distribution information with high spatial and temporal resolution at home and abroad. This research aimed at Jianli City, Hubei Province, where the summer harvest crops are most heavily affected. based on the antecedent precipitation indexes derived from meteorological station and the Sentinel-1A SAR data of the same period, the Kalman filter interpolation method was used to extract the temporal and spatial distribution information of the waterlogged summer crops with a time step of a day from 2018 to 2020. The methods is following：first, the spatial distribution information of the relative volumetric water content of the soil surface Layer (RVWCSSL) in the study area was extracted based on a Water-Cloud model and Sentinel-1A SAR data with a time step of 12 days. Then take the daily API(Antecedent Precipitation Index)data as observational data which with certain imprecise, the spatial distribution information of RVWCSSL extracted from Sentinel-1A SAR data were regarded as the estimated parameters, and the Kalman filter interpolation method was used to extract the spatial distribution information of RVWCSSL with a time step of a day. Finally the daily sub-surface waterlogging spatial distribution information was extracted based on daily spatial distribution of RVWCSSL values and according to the summer harvest crops waterlogging discriminant standard(if the duration that sliding 5 d mean of RVWCSSL values is higher than 95% was longer than 5 days, it is considered that the summer harvest crops are under mild waterlogging damage. If the duration is longer than 12 d, moderate waterlogging is considered to be suffered; Severe waterlogging is considered to be suffered if the duration is over 20 days). This method was verified on experimental area with an area of 220 hm2, using this method to calculate the RVWCSSL of experimental area, by compared with the actual observation value, the Nash-Stucliffe efficiency coefficient of the two is 0.909. At the same time, the temporal and spatial distribution of sub-surface waterlogging are also consistent with the field observation records, so it is feasible to use the Kalman filter interpolation method to extract the spatial distribution information of crop waterlogging. At the same time, through analyzing the extracted data, it was found that there is an obvious quadratic polynomial relationship between API index and the maximum value of the ratio of the crop sub-surface waterlogging area to the total area of summer crops in Jianli city; Since only precipitation changes with time, and the other factors are only related to location, the spatial distribution of waterlogging has little difference when the proportion of waterlogging is the same, which is conducive to accurate prediction of waterlogging. Since Sentinel-1A SAR data has the advantages of not being interfered by clouds and being available all day long. Meanwhile the precipitation index data can be calculated from the monitoring data of meteorological stations. This method of using satellite-ground integrated data to realize the high temporal and spatial resolution monitoring of crop sub-surface waterlogging can realize the operational operation of waterlogging disaster monitoring.