Author ORCID Identifier:
Date of Graduation
5-2026
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Environmental Dynamics (PhD)
Degree Level
Graduate
Department
Environmental Dynamics
Advisor/Mentor
Nalley, Lawton
Committee Member
Ashworth, Amanda
Second Committee Member
Tullis, Jason
Third Committee Member
Owens, Phillip
Keywords
Agriculture; Environment; Machine Learning; Remote Sensing; Sustainability
Abstract
Rapid environmental change is disrupting agricultural productivity, ecological function, and the long-term resilience of managed landscapes. At the same time, the rapid growth of geospatial data science has improved our understanding of environmental change and increasingly is being used to improve sustainability in agricultural and environmental management. However, critical gaps remain that limit the applicability of data-driven insights in landscape management. This dissertation investigates the potential of geospatial analytics for sustainable agriculture and landscape management, with a focus on applied methods that operate across spatial and temporal scales. Using field, landscape, regional, and national datasets, it explores the capabilities and constraints of machine learning, ground-based sensing, and remote observation techniques. The chapters of this dissertation demonstrate how machine learning enhances landscape analysis, how ground penetrating radar resolves fine-scale subsurface soil variability, and how remote sensing can quantify vegetative recovery and resilience over time at mine reclamation sites. Additional analyses identify data-driven and economically informed nutrient strategies in information-scarce regions and evaluate how climatic and environmental variability affects maize and soybean yield at scale. Together, these studies highlight how geospatial analytics at the agronomic-environment-nexus can support data-informed and data-driven land-use decisions across diverse production environments, resulting in more efficient and resilient land management systems.
Citation
Smith, H. W. (2026). Geospatial Science and the Changing Environment: Applied Methods for Sustainable Agriculture and Landscape Management. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/6130
