Ploughed field information is an important information for farming,and serves as the foundation for studying land use and land cover change.In this study,the Landsat TM image is data resource while the geometric features including characteristics of spectrums,compactness and smoothness are taken into account first.The use of regional growing method allows the multi-resolution segmentation of an image into highly homogeneous image objects polygon.Based on ground observed information,standard deviation of spectrums,shape index,density and asymmetric of objects polygon are chosen as identification characteristics and fuzzy function is used to define the types of ploughed field.In multidimensional feature space,we adopt nearest neighbor method to classify every object polygon.Based on classification,the same class of adjacency is combined,and then the area and the proportion of the ploughed field are calculated.The object-oriented method is adopted to extract boundary of Thailand farmland.The field examination of ground observation and analytical result indicate that class match rate is90.25%,area equal rate,90.25%and shape consistency,90%.