Land Cover Types Essay

Land Cover Types Essay

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In order to determine the band combination for maximum contrast between land-cover types depends on which land cover type is of interest. There are a number of different band combinations that are commonly used to highlight different features in a remotely sensed image. On the website of U.S. Geological Survey provides a brief explanation to the details of each band of the Landsat Thematic mapper, identifying the properties of each band and suggest the type of land cover that is the interest of study. Assuming the general land-cover type are vegetation, water, soil and urban areas. The band combination of MIR1 (Red), NIR (Green), Green (Blue) can provide maximum contrast between the different land cover types through the strong colour contrast. The bright green represents vegetation, the purple represents the urban areas or bare ground, and the blue colour represents water bodies. An example of the resulting map of the band combination described is shown in Figure 1 below.
To allow comparison between different band combinations, three other types of band combination of Landsat TM is shown in Figure 2 on the next page.

(Figure 1: Band combination of 5,4,3 of Landsat TM image of Pinjarra Hills. The green represents vegetation, purple is mainly representing urban areas or soil, blue represents the river.)

(Figure 2: Comparison between different band combinations with Landsat TM image. Top left: band 4,3,2. Top right: Band 7,5,4. Bottom left: Band 5,4,3. Bottom right: Band 4,5,3.)
The comparison above emphasise on the reason why the band combination rely on the choice of feature of interest. The different type of band of Landsat TM is sensitive to different biophysical properties of the features on the ground.  
Question 2.2 ...

... middle of paper ...

Natural Resources Canada 2012, Image Classification and Analysis, viewed 20/05/2014,
Richards, J.A. 2013, Remote sensing digital image analysis: an introduction, Springer Berlin Heidelberg, Berlin.
Schowengerdt, R.A. 2007, Remote sensing: models and methods for image processing, Academic Press, Amsterdam.
U.S. Geological Survey 2013, Frequently Asked Questions about the Landsat Missions, viewed 15/05/2014
Xie, Y, Sha, Z & Yu, M 2008, 'Remote sensing imagery in vegetation mapping: a review', Journal of Plant Ecology, vol. 1, no. 1, pp. 9-23.

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