To get the typical land cover information of urban area, present a method to get four typical land covers in study area by displaying three binary index images in RGB coordinate system without any algorithms. One scene Landsat TM image was used to calculate Normalized Difference Vegetation Index (NDVI), Negative Normalized Difference Vegetation Index (NNDVI) the paper present, and extract water information based on the spectral relationship of typical land objects. After compared the digital number of the typical land cover information of water, vegetation, impervious surface and soil in the three calculated layer, the four typical land cover information showed obvious differences. With carefully selecting appropriate threshold value for each index image, we obtained three binary images for water, vegetation and impervious surfaces. Then they were stacked to one image and assigned red to impervious surfaces, blue to water, and green to vegetation in a false color composite, and because the soil’s digital number was zero in the three binary images, it was shown black color automatically. Two hundred sample points were randomly selected for an accuracy assessment using high resolution ZY-3(China) image obtained at almost the same time as reference. The overall accuracy of the classification is 86% with the Kappa coefficient of 0.802. The result indicates that the method presented in this paper is feasible.