Landsat Thematic Images acquired at various intervals helps to measure the environmental changes. This paper presents a discrete wavelet based pixel level fusion of multitemporal landsat Thematic Mapper(TM) images of the same geographical area captured at periodic intervals to extract the essential information required to assess and monitor the changes occurred between the acquisition dates. The multispectral bands of the images were used in constructing the fusion decision map. The approximation coefficients of wavelet decomposition of the input images were averaged. The maximum intensity of the horizontal, vertical and diagonal coefficients among the input images were computed in constructing the fused image. The resultant fused image is analyzed based on the statistical measures such as relative mean difference, variation difference, contrast similarity and correlation coefficient. The experimental results show that the proposed approach is effective in fusing the satellite images for better image interpretation. © 2017 Institute of Advanced Scientific Research, Inc. All rights reserved.