Abstract: Rice chilling damage remains one of the major agricultural disasters in northeast China.Remote sensing technology can easily monitor this disaster on a relatively large scale.Satellites and ground multi-source data were used in this study to monitor rice delayed-type chilling damage by combining with extraction results of rice planting area, growth stage calculation and spatial distribution of static development stage.Based on these results, we can provide technical supports for the agricultural production sectors to monitor rice chilling damage in the wide area and to improve rice quality and yield.Using remote sensing data, daily mean temperature of 196 meteorological stations located in northeast China from 2000 to 2009, rice development stages and related geographic information data, the degree of rice chilling damage and main year of chilling damage were analyzed according to technical specifications for evaluation of rice cold damage.The information of rice planting area was extracted by the products of MODIS MCD12Q1 and Landsat data.Normal differential vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were acquired from the products of MODIS MCD12Q1.The reference range of NDVI and EVI for development stages of rice was divided by the method of statistical analysis.According to the correlation between Julian days of rice development stages and geographical factors, the regression equations of rice development stages were constructed.On the basis of the equations, daily distribution maps of development stages were obtained by a piece of sliding filter board through ENVI+IDL.Finally, monitoring of rice delayed-type chilling damage was done based on remote sensing in northeast China on May 24, 2009 and August 7, 2009.The results showed that the large-range distribution of damage happened in 2002, 2003, 2008 and 2009 in northeast China.Heilongjiang province was particularly affected by the disaster.Also, both of NDVI and EVI values of rice in each development stage obeyed the normal distribution.But the accuracy rate of EVI values in determining the rice development stages was over 76%.Obviously, EVI values were more effective than NDVI values in detecting rice phenology.In addition, rice development stage models were established according to the relationship between longitude, latitude, altitude and day series.The dates of simulated rice development stages were earlier than the actual observation dates as a whole with an error of 1 to 3 days.And the difference days in simulated results and observed values were much smaller than that between two rice development stages.The estimate accuracy can meet the need of the research.Moreover, on the basis of models, we made the spatial distribution maps of every static development stage and answered how to confirm the ownership of the rice development stages by infinite function.Finally, rice delayed-type chilling damage was dynamically monitored in two days by using this method.The monitoring results had a better consistence with the observational records in time and space.