Digital satellite remote sensing and Geographic Information Systems (GIS) have been used in conjunction with the Universal Soil Loss Equation (USLE) to model soil erosion potential within watersheds. This study compared erosion estimates calculated by the remote sensing method to results obtained in the field by soil conservationists using conventional methods.

Predictive models have established a niche in the field of archaeology. Valued as tools in predicting potential archaeological sites, their use has increased with development of faster and more affordable computer technology. Predictive models highlight areas within a landscape where archaeological sites have a high probability of occurrence. Therefore, time and resources normally expended on archaeological exploration can then be more efficiently allocated to specified locations within a study area. In addition to the resulting predictive surface, these models also identify significant variables for site selection by prehistoric or historic groups. Relationships with the environment, whether natural or social, are extremely pertinent to strengthening the resource base. In turn, this information can be utilized to better interpret and protect valuable cultural resources. A predictive probability model was generated to locate Union Civil War fortifications around Petersburg, Virginia. This study illustrated the ease with which such analysis can be accomplished with the integrated use of a Geographic Information System with statistical analysis. Stepwise logistic regression proved effective in selecting significant independent variables to predict probabilities of fortifications within the study area, but faired poorly when applied to areas withheld from the initial building stage of the model. Variation of battle tactics between these two separate areas proved great enough to have a detrimental effect the model's effectiveness. / Master of Science

Over the past half century, archaeologists have been interested in how the environmental variation of the Central Coast has affected settlement patterns. Archaeologists relied on ethnography and subsistence models to explain settlement distribution but were unable to analytically demonstrate influencing factors. The objectives of this thesis were to investigate: (1) the spatial arrangement of sites to examine the types of locations people utilized; and (2) test if the occupational history of a site is reflected by its geographic locations. In this project, site dimension was used as a relative indicator of settlement occupational intensity, and over twenty environmental attributes were tested. Analysis was systematically conducted at multiple spatial scales using GIS. In the first stage the location of shell middens (n=351) were compared against an environmental baseline, derived from a sample of random points. For the second stage, small and large shell middens were compared to test if their locations significantly differed. It was found that shell middens do show an association with certain environmental settings. For some attributes, there was an observable difference in the location of large and small shell middens. However, immense variability was identified and the environmental context of sites greatly determined whether locational preferences could be empirically demonstrated. Overall, large middens, more so than small middens, are located in areas with higher resource diversity. These conclusions support other studies that indicate the relevance of multiple determinants and emphasizes the local nuances of settlement patterning affected by environmental and cultural factors. My results oppose the simplistic and static notion about a prehistoric annual cycle of sedentary winter villages and seasonal resource-specific camps. Improvements to an understanding of settlement distribution can aid in contextualizing specific sites within their regional setting and contribute to our knowledge regarding larger cultural practices such as subsistence and land use practices. / Thesis / Master of Arts (MA)

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Route reconnaissance has been valuable for military commanders for centuries. Engineering forces are specifically tasked to gather route reconnaissance intelligence to present to the maneuver commander. US Army Engineers presently use a variety of highly technological methods to collect, process, and present this detailed route reconnaissance intelligence. This thesis examines and analyzes the capabilities of four reconnaissance groups. Using a matrix, each of the four units is ranked based on surveys of reconnaissance officers and on the personal experience of the author of this thesis. Results show that Unit 2 (FEST-M) is the most qualified unit to collect detailed geospatial route reconnaissance of the battlefield. The ARRK/TETK software system has helped this unit rise to the top over the other reconnaissance unit types analyzed. The need for geospatial route reconnaissance will continue to be a part of the modern day battlefield and will change constantly as technology is updated.

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No description available.