To determine the combination of bands for maximum contrast between land cover types depends on which land cover type is of interest. There are several combinations of bands commonly used to highlight different features in a remote sensing image. A brief explanation of the details of each band of the Landsat thematic mapper is provided on the US Geological Survey website, identifying the properties of each band and suggesting the type of land cover that is of study interest. Assuming the general land cover type consists of vegetation, water, soil and urban areas. The band combination of MIR1 (red), NIR (green), green (blue) can provide maximum contrast between different land cover types through strong color contrast. Bright green represents vegetation, purple represents urban areas or bare ground, and blue represents bodies of water. An example of the resulting map of the described band combination is shown in Figure 1 below. To allow comparison between different band combinations, three other types of Landsat TM band combinations are shown in Figure 2 on the next page. (Figure 1: Combination bands of 5,4,3 of the Landsat TM image of the Pinjarra Hills. Green represents vegetation, purple represents mainly urban areas or soil, blue represents river.) (Figure 2: Comparison of different band combinations with the Landsat TM image. Top left: band 4,3,2. Bottom left: band 5,4,3 right: band 4,5,3.) The above comparison highlights why the band combination is based on the choice of the feature of interest. Landsat TM's different band type is sensitive to different biophysical properties of terrain features. Question 2.2 ...... middle of paper ...... 5/2014, Natural Resources Canada 2012, Image Classification and Analysis, viewed 05/20/2014, Richards, JA 2013, Digital Image Analysis with remote sensing: an introduction, Springer Berlin Heidelberg, Berlin.Schowengerdt, RA 2007, Remote sensing: models and methods for image processing, Academic Press, Amsterdam.US Geological Survey 2013, Frequently asked questions about Landsat missions, accessed 05/15 /2014Xie, Y, Sha, Z and Yu, M 2008, 'Remote sensing imagery in vegetating mapping: a review', Journal of Plant Ecology, vol. 1, no. 1, pages. 9-23.