Date of Award

Spring 2022

Document Type

Thesis

Degree Name

Master of Science (MS) in Geographic Information Science & Technology

Department

Chemistry & Geosciences

Committee Chair

Dr. Mark Sciuchetti

Abstract

Environmental degradation is a destructive force produced by the human disturbance of pollution. It is a phenomenon that gradually evolves landscapes over time resulting in irreversible outcomes. Environmental degradation physically affects spaces’ resources, objects, and inhabiting humans. This study observes the impacts of pollution beyond physical boundaries and how it affects human identity/sense of place through the utilization of geographic information systems. Specifically, it examines cultural identity developed through human experiences and connections to landscapes containing water resources. Following, pollution contaminates water resources disrupting experiences and connections thus causing the cultural identity to disappear. The case study applied to this research is the Alabama cultural identity connected to the Tennessee River that flows through the northern portion of North Alabama.

Alabama citizens formulate deep connections to landscapes through farming, attaching religious symbolism to the environment through biblical references, and perform Christian practices with objects found in spaces (Tuan, 1974). Due to the contamination in the Tennessee River, this affects utilization of water for farming and Christian practices performed in the river because of the threat pollution poses. As a result, Alabama cultural identity disappears halt of experiences against an unfamiliar landscape degraded by pollution. Testing this hypothesis, this research utilizes a mixed methods approach applying multiple analyses and models.

Participatory observations, surveys, and interviews accomplished the qualitative analysis of Alabama culture. Then, the collection of multiple amounts hydrological data, survey statistics, interviews, poverty data and land use data were inputted into the geographically weighted regression model completing the quantitative analysis of water pollution. The model that was implemented was the Arc Story Map. Then, Arc Story Map presented the data visually for the public.

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