prac_2 - LSGI332 Remote Sensing Assignment 1: problem-based...

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LSGI332 Remote Sensing Assignment 1: problem-based learning assignment Materials: ErMapper software Last week’s lab sheet with instructions on how to display a greyscale image, zoom, pan, and use the Cell Values Profile to obtain the pixel values, and Algorithm Geoposition Extents . Landsat ETM+ image of 17 th September 2001 acquired at 9.45am local time Landsat_Sept2001_Ts.ers. This is a Landsat thermal image (band 6) of Landsat Enhanced Thematic Mapper Plus (ETM+). The temperature values are in degrees Kelvin. The spatial resolution is 60m. IKONOS images accessed via Google Earth if you need to identify land cover types in Kowloon on Hong Kong island Roads vector layer: Road_kl.erv – for more precise location purposes (if necessary) Procedure 1. Load a greyscale algorithm into ErMapper as you did last week and read the Landsat thermal image into it. To enhance the brightness you may need to use the 99% contrast enhancement button and re-apply it after zooming in or out
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This note was uploaded on 03/22/2010 for the course GEOMATICS LSGI taught by Professor Kady during the Spring '07 term at Hong Kong Shue Yan.

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prac_2 - LSGI332 Remote Sensing Assignment 1: problem-based...

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