First Advisor

Martin Swobodzinski

Term of Graduation

Spring 2026

Date of Publication

8-20-2026

Document Type

Thesis

Degree Name

Master of Science (M.S.) in Geography

Department

Geography

Language

English

Subjects

Citizen Science, Human-wildlife Interactions, Spatial Analysis, Statistical Analysis, Urban Coyotes, Volunteer Geographic Information (VGI)

Physical Description

1 online resource (xii, 144 pages)

Abstract

As coyotes increasingly adapt to urban environments, understanding their interactions with humans is becoming a significant issue in the fields of animal and urban geography. This study examined the spatial and temporal patterns of citizen-reported coyote sightings in the Greater Portland area, utilizing data from the Portland Urban Coyote Project (PUCP). It also explored the relationship between environmental and socioeconomic factors and citizens' coyote sightings. Environmental factors analyzed included land cover and tree canopy height, while socioeconomic variables examined comprised road infrastructure, median household income, and population density. These factors were assessed within a uniform 1,500 by 1,500-foot grid system.

A variety of statistical and spatial methods were employed, including descriptive statistics, Pearson's chi-square test, Principal Component Analysis (PCA), and Negative Binomial Regression (NBR). Spatial techniques used included Average Nearest Neighbor, Incremental Spatial Autocorrelation, Getis-Ord Gi*, and Kernel Density analysis. The results indicate that there are no clear temporal patterns in coyote sightings. However, spatial analysis reveals that sightings are clustered in areas with a higher human presence, particularly near urban green spaces such as parks.

These findings suggest that reported coyote sightings are influenced by both habitat characteristics and human activity, including awareness of the project. While Volunteered Geographic Information (VGI) offers valuable insights and fosters public engagement, the results also underscore important limitations concerning data quality, methods, and reporting bias.

Rights

© 2026 Ha Ngan Pham

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Persistent Identifier

https://archives.pdx.edu/ds/psu/45115

Available for download on Friday, August 20, 2027

Included in

Geography Commons

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