Date of Award

Spring 6-13-2025

Document Type

Masters Capstone Project

Degree Name

M.S. in Geographic Information Science

Organizational Unit

College of Natural Science and Mathematics, Geography and the Environment

First Advisor

Steven Hick

Copyright Statement / License for Reuse

All Rights Reserved
All Rights Reserved.

Keywords

Solar panels, Geographic weighted regression, Zip code, Census data, Socioeconomic

Abstract

This capstone project seeks to find the relationship between socioeconomic and demographic variables and their relationship to residential photovoltaic installations across New Jersey. The study consists of Geographic Weighted Regression Analyses to construct and socioeconomic index indicating the likelihood of photovoltaic adoption in New Jersey zip codes. Then using the index to predict future photovoltaic adoption across the state. The study found that socioeconomic and demographic variables can predict photovoltaic adoption within one year, but when placed in an index and used to predict future adoption trends, the model under predicts and extremely over predicts. While socioeconomic status is a contributing factor to photovoltaic adoption there is a more complex relationship between status and local adoption trends.

Copyright Date

6-9-2025

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Brandon McAlister

Provenance

Received from author

File Format

application/pdf

Language

English (eng)

Extent

49 pgs

File Size

1.7 MB

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