Digital Commons Network^™

The Value Of Farmland: Mapping Assessor Data To Understand Land Use Change, Lyndi Perry

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Ideas developed by regional economists have potential applications within the urban planning field. One potential application is toward conserving farmland, and within this thesis this topic is examined for the study area of Utah County, Utah. Using assessor data, a land value map is created and further used to develop a regional economic model and spatial models that were analyzed for patterns of land use change.

Findings show that representing land value as continuous surface maps is a useful approach. The maps reveal that Utah County has densified as its population increased while farmland loss still occurred in agriculturally-important areas. …

Assessment Of Potential Changes In Crop Yields In The Central United States Under Climate Change Regimes, Neil Matthews-Pennanen

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Climate change is one of the great challenges facing agriculture in the 21^st century. The goal of this study was to produce projections of crop yields for the central United States in the 2030s, 2060s, and 2090s based on the relationship between weather and yield from historical crop yields from 1980 to 2010. These projections were made across 16 states in the US, from Louisiana in the south to Minnesota in the north. They include projections for maize, soybeans, cotton, spring wheat, and winter wheat.

Simulated weather variables based on three climate scenarios were used to project future crop …

Random Forests Applied As A Soil Spatial Predictive Model In Arid Utah, Alexander Knell Stum

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Initial soil surveys are incomplete for large tracts of public land in the western USA. Digital soil mapping offers a quantitative approach as an alternative to traditional soil mapping. I sought to predict soil classes across an arid to semiarid watershed of western Utah by applying random forests (RF) and using environmental covariates derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and digital elevation models (DEM). Random forests are similar to classification and regression trees (CART). However, RF is doubly random. Many (e.g., 500) weak trees are grown (trained) independently because each tree is trained with a new randomly …