The presence of these factors must be taken into consideration as they relate to the specific area being surveyed. A complete study of these factors and their potential affects on the ability to use remote sensing techniques will have to be explored in order to understand how they affect the use of satellite for remote sensing in Malawi.
The use of thermal infrared (TIR) data from ASTER spaceborne instrumentation was used successfully to detect surface temperature anomalies in the Coso geothermal field in eastern California (Eneva, Coolbaugh, & Bjornstad et al., 2007, pp. 335). One of the key difficulties that was found in the use of TIR data from ASTER is that thermal inertia from different types of vegetative matter can make true geothermal anomalies difficult to identify using spaceborne data alone (Dudley-Murphy & Nash, 2003, p. 645). A study of the thermal inertia of the plant material in Malawi would have to be undertaken so that its affects could be subtracted out of the data in order to detect geothermal anomalies in the area to be surveyed.
Items Affecting Signal Strength and Clarity
As with any spectroscopy technique, a number of elements can affect the ability to detect the desired target. In the laboratory, one has better control over these elements. For instance, one can inject a known gas into the tube, control temperature and take steps to eliminate known contaminants. However, this is more difficult in the natural setting. Spectroscopy techniques from space work in a similar fashion to those in the laboratory except for one important element. Analyses conducted from space do not afford the ability to control the environment in which the analysis is performed. There are a number of factors that can affect the signal and the accuracy of the analysis when it is performed from space. The following will examine these factors and their affect on the ability to perform an accurate assessment.
. Vegetation appears to present one of the key difficulties in anomaly mapping for geothermal exploration. Geobotanical anomalies may accompany mineral deposits and hydrothermal convection systems (Nash & Hernandez, 2001, pp. 1). Therefore, vegetation may not represent unwanted interference all of the time, but may be the clue needed to confirm the anomaly. The affects of vegetation in Malawi will have to be studied to determine the importance of potential interference to signal strength, impedance and phase shift. Colinearity of certain mineral mixes may also have an impact on the spectra. In the case of calcium carbonate, this anomaly caused by colinearity of the complex mixture indicates hydrothermal convection (Nash & Johnson, 2002, pp. 8). In a study conducted in Turkey, mineral identification was impeded by areas of cloudiness as well as dense forests (Dogan, 2008, pp. 224). Geothermal activity may also be responsible for flow patterns in glaciers and ice sheets in Iceland (Bourgeois, Dauteuil, & Vliet-Lanoe. 1999. pp. 74).
Other factors were found to affect the ability to detect geothermal temperature fluctuation anomalies, including elevation and other topographical features, making it difficult to distinguish surface fluctuations from subsurface anomalies (Eneva & Coolbaugh, 2009, pp. 467-470). A comparison of daytime and nighttime images reveals that these comparisons can be an important tool in distinguishing true subsurface geothermal anomalies from surface and atmospheric interference. However, much more work is needed in this area to understand the application of these paired data sets (Eneva, Coolbaugh, & Bjornstad et al., 2007, pp. 1-7).
The pixel in the hyperspectral data set represents a combination of the end-member materials, with those of areal abundance representing the pixel color. However, each pixels distinct and must be analyzed further to determine of indicator minerals for geothermal hotspots are present (Kratt, Calvin & Coolbaugh, 2005, pp. 271-276). This will be an important area for further development of spectral techniques, as many minerals have similar absorption features, as was the case with chalcedony and opal in a recent analysis (Kratt, Calvin, & Coolbaugh, 2004, pp. 1304). Current efforts in research are focusing on the ability to unmix spectra and cancel the affects of atmospheric interference through the use of algorithms (Pal & Nash, 2003, pp. 669-672).
Spectral analysis using wavelengths of 0.4 to 2.5 ?m have been used as the means to identify spectral signatures in the laboratory. These same analysis techniques are now being used in spaceborne methods of spectral analysis (Kratt, Calvin & Lutz, n.d. pp. 1-9). At the present time, these results are being confirmed using handheld GPS and pocket...
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