Social and Behavioral Sciences Commons^™

Bedrock Geological Map Of The Rockhouse Quadrangle, Carroll And Madison Counties, Arkansas, Douglas Eben Jones

Graduate Theses and Dissertations

A digital geologic map of the Rockhouse quadrangle, Carroll and Madison counties, Arkansas, was created on a 1:24,000 scale using ArcMap 10 and Photoshop CS4. The data obtained in the field are digitized onto the United States Geological Survey (USGS) digital raster graphic (DRG) of the Rockhouse quadrangle. The geology in the Rockhouse quadrangle consist entirely of sedimentary rocks that are Paleozoic ranging from Lower Ordovician to Mississippian in age. The Ordovician System is represented by the Cotter, Powell, Everton, and St. Peter Formations. The Cotter and Powell are the prominent bluff forming units throughout the quadrangle and along the …

A Geomechanical Study Of The Mississippian Boone Formation, Karen Nicole Mason Buckland

Graduate Theses and Dissertations

The Boone Formation in northwest Arkansas is a chert-limestone sequence analogous to the subsurface Mississippi Lime reservoir in parts of Oklahoma and Kansas. It has low permeability and produces via horizontal drilling and hydraulic fracturing. The response to stimulation by fracturing is dependent on the quantity of chert in the area. Chert nodules and laterally extensive chert layers in the sequence are variable. Locally, cm- to dm-scale chert bedding is continuous and comprises up to 50% of the outcrop. Elsewhere, the chert is nodular and intermittent.

Samples collected from representative outcrops spanning the thickness and aerial extent of the formation …

Classification Of Satellite Time Series-Derived Land Surface Phenology Focused On The Northern Fertile Crescent, Brian Embree Bunker

Graduate Theses and Dissertations

Land surface phenology describes events in a seasonal vegetation cycle and can be used in a variety of applications from predicting onset of future drought conditions, to revealing potential limits of historical dry farming, to guiding more accurate dating of archeological sites. Traditional methods of monitoring vegetation phenology use data collected in situ. However, vegetation health indices derived from satellite remote sensor data, such as the normalized difference vegetation index (NDVI), have been used as proxy for vegetation phenology due to their repeated acquisition and broad area coverage. Land surface phenology is accessible in the NDVI satellite record when images …

Agricultural Production And Stability Of Settlement Systems In Upper Mesopotamia During The Early Bronze Age (Third Millennium Bce), Tuna Kalayci

Graduate Theses and Dissertations

This study investigates the relationship between rainfall variation and rain-fed agricultural production in Upper Mesopotamia with a specific focus on Early Bronze Age urban settlements. In return, the variation in production is used to explore stability of urban settlement systems. The organization of the flow of agricultural goods is the key to sustaining the total settlement system.

The vulnerability of a settlement system increases due to the increased demand for more output from agricultural lands. This demand is the key for the success of urbanization project. However, without estimating how many foodstuffs were available at the end of a production …

Landscape Epidemiology And Machine Learning: A Geospatial Approach To Modeling West Nile Virus Risk In The United States, Sean Gregory Young

Graduate Theses and Dissertations

The complex interactions between human health and the physical landscape and environment have been recognized, if not fully understood, since the ancient Greeks. Landscape epidemiology, sometimes called spatial epidemiology, is a sub-discipline of medical geography that uses environmental conditions as explanatory variables in the study of disease or other health phenomena. This theory suggests that pathogenic organisms (whether germs or larger vector and host species) are subject to environmental conditions that can be observed on the landscape, and by identifying where such organisms are likely to exist, areas at greatest risk of the disease can be derived. Machine learning is …