A decision tree algorithm was developed to classify the freeze/thaw status of the surface soil based on the cluster analysis of samples such as frozen soil

thawed soil

desert and snow

along with microwave emission and scattering characteristics of the frozen/thawed soil.The algorithm included five SSM/I channels（19V

19H

22V

37V

85V）and three crucial indices including scattering index

37GHz vertical polarization brightness temperature and 19GHz polarization difference

and took into consideration the scattering effect of desert and precipitation.The pureness of samples is essential to the analysis of the microwave brightness temperature characteristics

which is prior to deciding the thresholds of each node of the decision tree.We have selected four types of samples

including frozen soil

thawed soil

desert and snow.The frozen soil has some special microwave emission and scattering characteristics different from the thawed soil:① lower thermodynamic temperature and brightness temperature;② higher emissivity;③ stronger volume scattering

and the brightness temperature decreased with increasing frequency.The threshold of each node of the decision tree can be determined by using cluster analysis of three vital indices

and calculating the average and standard differences of each type and each index.The 4cm-depth soil temperature on the Qinghai-Tibetan Plateau observed by Soil Moisture and Temperature Measuring System of GEWEX-Coordinated Enhanced Observing Period

were used to validate the classification results.The total accuracy can reach about 87%.A majority of misclassification occurred near the freezing point of soil

about 40% and 73% of the misclassified cases appeared when the surface soil temperature is between-0.5—0.5℃ and-2.0—2.0℃

respectively.Furthermore

the misclassification mainly occurred during the transition period between warm and cold seasons

namely April-May and September-October.Based on this decision tree

a map of the number of frozen days during Oct.2002 to Sep.2003 in China was produced by composing 5 days classification results due to the swath coverage of SSM/I.The accuracy assessment for pixels with more than 15 frozen days（less than 15 meaning the short time frozen soil）was carried out with the regions of permafrost and seasonally frozen ground in map of geocryological regionalization and classification in China as reference data（Zhou et al.

2000）

and the total classification accuracy was 91.66%

while the Kappa coefficient was 80.5%.The boundary between frozen and thawed soil was well consistent with the southern limit of seasonally frozen ground.A long time series surface frozen/thawed dataset can be produced using this decision tree

which may provide indicating information for regional climate change studies

regional and global scale carbon cycle models

hydrologic model and land surface model so on.