GIS and Remote Sensing

Gregory Vandeberg

University of North Dakota

	Spatial Analysis of Soil Metal Levels from Anaconda, Montana.      The processing and smelting of metallic ores (primarily copper) occurred in the Anaconda, Montana, area from approximately 1884 through 1980.  These activities have contributed to the contamination of area soils, surface water and ground water from aerial emissions and waste disposal.  Elevated levels of arsenic and other contaminants such as cadmium, copper, lead and zinc are present in soil and/or water throughout Anaconda and in other communities of western Silver Bow County, and Deer Lodge County, Montana. Much of the area is now part of the Anaconda Smelter Superfund site. The objective of this study was to examine the spatial patterns of the magnitude and extent of soil arsenic, copper, lead and zinc values in the Anaconda area.  Data from numerous superfund investigations were analyzed for clustering of soil metal levels using Ripley’s K-function.  The data were further analyzed using the Gi*(d) statistical model to investigate local spatial autocorrelation of soil metal levels at 300 and 600 m distances.  The results indicate that much of the data are clustered in regards to soil metal levels.  Several elevated soil metal hot spots were identified using Gi*(d) for each of the metals.  These hot spot locations varied depending upon the metal analyzed. The figure at left shows the clustering of arsenic at 300 and 600 m separation distances.
	Identification And Characterization Of Mining Waste Using Landsat Thematic Mapper Imagery, Cherokee County, Kansas Abstract: Mining wastes and tailings are present throughout much of the world and United States including the Tri-State lead and zinc mining district in southeastern Kansas, southwestern Missouri, and northeastern Oklahoma.  These wastes and tailings are often associated with heavy metals, acid mine drainage, and other physical hazards.  Many tools have been utilized and proposed for the rapid inventory and characterization of these wastes including the use of Landsat Thematic Mapper (TM) images.  A Landsat TM image of the Cherokee County, Kansas portion of the Tri-State mining district was evaluated in an attempt to inventory mining waste and tailings in the county, and characterize the gross mineralogy of these wastes.  False color TM composites were used to perform supervised and unsupervised landcover classifications of Cherokee County to identify the locations of mining waste and tailings.  In addition, several TM band combinations (mineral indices) were used to characterize the mineralogy of these wastes.  The accuracy of the classifications in identifying mining wastes from other land types was less than 60 percent.  However, false color composites of Landsat TM bands were a useful tool in identifying these wastes, and determining their gross mineralogy. The figure at left shows a Landsat TM image of Cherokee County, KS (bands 7-4-2).
	The figure at left shows a supervised classification of mining wastes (yellow) in Cherokee County, Kansas using Landsat TM imagery (1992) and bands 7-4-2.

  Last revised February 2007
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