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Submitted by:
Larry A. Costick, Susan L. Ustin, and Wesley W. Wallender
Center for Spatial Technologies and Remote Sensing (CSTARS)
Hydrologic Science Section, Department of Land, Air, and Water Resources
University of California, Davis, CA 95616
In order to read the entire report download
mine0721.pdf
This file is 4.56 MB of photos, maps and text.
You will need Adobe Acrobat 3.0 which is
free at:
Mineral libraries provided
by JPL/USGS SpecLab.
through the curtsey of Roger Clarke
http://speclab.cr.usgs.gov
The GIS coverages presented
in this paper have been provided by Karen
Beardsley, Kaylene Keller,
and Andi Thode of the Information Center for
the Environment, more of
their work may be found
at: http://ice.ucdavis.edu/ and if your interested
in maps of California
natural resources look at:
http://ice.ucdavis.edu/ice_maps/
Introduction:
Use of remote sensing to map geologic formations and mineral exposures began soon after the launch of the first Landsat satellites. A new generation of satellites is approaching with many new capabilities that can improve resource management and monitoring. There will be 50 or more non-military land-observing satellites, launched by commercial ventures and many governments in this decade. These sensors are more powerful than existing Landsat satellites; some will obtain one to five meter ground resolutions and others will measure new parts of the electromagnetic spectrum. In August 1997 TRW will launch the first space borne imaging spectrometer, the Lewis satellite with 385 contiguous spectral channels measuring the visible and reflected infrared spectrum. This high spectral resolution sensor will be able to measure the specific absorption features that characterize many minerals and geologic materials, making their unique identification possible. Currently, there are three research grade airborne sensors that have similar capabilities, and we provide several examples in this report of this potential. Specifically we have used examples provided by NASA's Advanced Visible Infrared Imaging Spectrometer, AVIRIS. This airborne sensor has 224 spectral bands in the 400-2500 nm wavelength range (the visible and reflected infrared spectrum) and has nominal pixel resolution of 20 meters. For contrast the Landsat Thematic Mapper, TM satellite has six spectral bands in this region and 30 meter pixels. The purpose of this report is to provide an initial assessment of ways in which these satellite and airborne sensors can contribute to mapping and monitoring mine sites and environmental hazards.
Techniques to extract spectral information have ranged from visual assessment of simple false color composites to more sophisticated mathematical transformations of the data. Newer imaging spectrometers require more experience to extract the full potential of the information embedded in the remote sensing data. In this report we highlight several analytical methods useful for detecting mine sites and mineral analysis. Monitoring and evaluation of geological conditions and hazardous wastes using remote sensing almost inevitably requires some assessment of vegetation condition or land cover disturbance, typically either observing poor vegetative growth or bare zones.
Many mines or mineral outcrops or contaminant sources have small point-source locations within a larger geologic and ecological context. Often the goal is to identify these point sources due to their contrast with the surrounding vegetation and terrain. Numerous factors create variability in satellite images that are imposed at multiple scales. Topographic patterns, illumination conditions, and atmospheric composition at the time of measurement are factors that vary at larger spatial scales and need to be accounted for in the analysis. Of the factors affecting local scale are evidence of disturbance, low or no vegetation cover, and changes in vegetation distribution.
Interpretation of remote sensing images typically can be improved by linking analysis with a geographic information systems (GIS) database. Often only simple image analysis procedures are needed to extract information when combined with other spatial data, which overlays with mine site locations can provide. Because the department has a mines location database, this information will allow overlaying the site locations over the image to detect evidence for correct identification of mine locations, apparent size and extent of tailings and disturbance, evidence for erosion, and off-site transport. Digital elevation maps (DEM) can be readily combined with image data sets to assess topographic patterns and how this affects potential losses or other problems with mine sites.
In addition to spectral methods, there are a number of methods to examine images for texture or spatial patterns in vegetation distribution that can be combined with ancillary data to improve predictions of site condition. Anomalous linear features in an image, e.g., joints and fault lines are often associated with zones of higher soil permeability, and often have different plant species or changes in plant density growing over fracture zones making them stand out in the imagery This image is a portions of a Landsat 5 TM scene projected in false color. Known mining sites both active and abandon have been located via GPS to be used as part of our AVIRIS training set. 1997 AVIRIS imagery of this area has just become available. Click in the image to see the larger version.
