Page 130 - Introduction to Mineral Exploration

6: REMOTE SENSING 113

BOX 6.1 Some sources of remotely sensed data.

• US Geological Survey 1981. Worldwide directory of national earth science agencies and related
international organizations. Geological Survey Circular 834, USGS, 507 National Center, Reston,
Virginia, 22092, USA. http://www.usgs.gov and http://glovis.usgs.gov/
• SPOT-Image, 18 avenue Eduoard Belin, F31055, Toulouse Cedex, France. http://www.spot.com
• Meteorological satellite imagery.
US Department of Commerce, NOAA/NESDIS/NSDC, Satellite Data Services Division (E/CCGI),
World Weather Building, Room 10, Washington DC, 20233, USA http://db.aoml.noaa.gov/dbweb/
• Landsat (pre-September 1985).
US Geological Survey, EROS Data Center (EDC), Mundt Federal Building, Sioux Falls, South Dakota,
57198, USA
• Landsat (post September 1985).
Earth Observation Satellite Company (EOSAT), 1901 North Moore Street, Arlington, Virginia, 22209,
USA. http://edcimswww.cr.usgs.gov/pub/imswelcome/
• Landsat imagery is also available from local and national agencies and free from the GLCF.
http://glcf.umiacs.umd.edu/intro/landsat7satellite.shtml
• Infoterra, Europa House, The Crescent, Southwood, Farnborough, Hampshire, GU14 0NL, UK.
http://www.infoterra-global.com

exploration program are: image restoration, 1 Contrast enhancement. An image histogram
image enhancement, and data extraction has already been described in section 6.2.3
(Sabins 1997). Drury (2001) explains the (Fig. 6.4). A histogram of a typical untrans-
methods of digital image processing in more formed image has low contrast (Fig. 6.4a) and
detail and shows how they can be applied to in this case the input gray level is equivalent
geological remote sensing. to the transformed gray level (Schowengerdt
1983, Drury 2001). A simple linear transforma-
tion, commonly called a contrast stretch, is
Image restoration
routinely used to increase the contrast of a dis-
Image restoration is the process of correcting played image by expanding the original gray
inherent defects in the image caused during level range to fill the dynamic range of the
data collection. Some of the routines used to display device (Fig. 6.4b).
correct these defects are: 2 Spatial filtering is a technique used to
1 replacing lost data, i.e. dropped scan lines or enhance naturally occurring straight feature
bad pixels; such as fractures, faults, joints, etc. Drury
2 filtering out atmospheric noise; (2001) and Sabins (1997) described this in more
3 geometrical corrections. detail.
The last named correct the data for carto- 3 Density slicing converts the continuous
graphic projection, which is particularly im- gray tone range into a series of density intervals
portant if the imagery is to be integrated with (slices), each corresponding to a specific digital
geophysical, topographical, or other map-based range. Each slice may be given a separate color
data. or line printer symbol. Density slicing has
been successfully used in mapping bathymetric
variations in shallow water and in mapping
Image enhancement
temperature variations in the cooling water of
Image enhancement transforms the original thermal power stations (Sabins 1997).
data to improve the information content. Some 4 False color composite images of three bands,
of the routines used to enhance the images are e.g. MSS bands 4, 5, and 7, increase the amount
as follows: of information available for interpretation.