Remote sensing, with its capacity to capture continuous, high spatial and spectral resolution data, has emerged as an invaluable tool for ecological research and addressing conservation challenges. To fully harness the potential of remote sensing, spectral ecology has emerged as a field that investigates the interactions between the electromagnetic spectrum and biological processes. This dissertation capitalizes on a model system to explore the spectral ecology of a dominant, highly polymorphic, keystone, and endemic tree species (Metrosideros polymorpha). M. polymorpha not only serves as a model organism for studying adaptive radiation and intraspecific variation but also presents a critical conservation challenge. The recent introduction of the fungal disease Ceratocystis lukuohia has resulted in millions of M. polymorpha mortalities. This dissertation employs leaf-level spectroscopy data and canopy-level imaging spectroscopy data. Imaging spectroscopy captures reflectance across the visible to short-wave infrared (VSWIR) spectrum to provide high-spectral resolution data that enable canopy trait retrievals, species classifications, disease resistance detection, and genotype differentiation. Chapter 1 serves as an introduction, framing the subsequent chapters by presenting an overview of spectral ecology, imaging spectroscopy, and M. polymorpha. Chapter 2 explores M. polymorpha trait and spectra variation across environmental gradients. This chapter concludes that intraspecific variation follows the leaf economic spectrum and that elevation is a dominant driver of M. polymorpha trait and spectral variation. In Chapter 3, leaf-level spectroscopy was able to discriminate between sympatric, conspecific varieties of M. polymorpha and their hybrids as well as individuals resistant and susceptible to Ceratocystis wilt. Together, Chapters 2 and 3 support the concept of “genetic turnover,” akin to species turnover, wherein environmental conditions filter M. polymorpha genotypes present in a given region. Chapter 4 classifies M. polymorpha across the over 10,000 km2 of Hawai'i Island to aid in conservation efforts, demonstrating the potential of imaging spectroscopy to classify vegetation on large geographic scales. The final chapter builds on the prior chapters to present a M. polymorpha genetic diversity map for Hawai'i Island. In conclusion, this dissertation examines the spectral ecology of a model system to advance the understanding of ecological dynamics and address a pressing conservation challenge.

Quantifying ecological relationships by gathering and sifting through large stores of data and applying statistical models to them is a substantial first step in identifying optimal habitat for the dispersal of threatened species, but the implementation of the result requires coordination between political, economic, and environmental actors that are further complicated by the margin of error in modeling a wildlife corridor. That is why the partnership between Arizona State University (ASU), the Phoenix Zoo: Arizona Center for Nature Conservation, the National Aeronautics and Space Administration (NASA) DEVELOP, and Osa Conservation needed a framework for identifying and analyzing the forest patches that constituted the least cost path (LCP) modelled to connect the Talamanca Mountains of La Amistad International Peace Park and the Osa Peninsula of Corcovado National Park and allow for the dispersal of jaguars (Panthera onca). A framework for selection of forest patches of adequate size was established in ArcMap and data were extracted to further analyze their characteristics and select targets to be ground-truthed. Forest patches were successfully identified and selected using data used for the modelling of the LCP. Patches were selected by the desired size of three hectares or greater, the home range of prey species paca (Cuniculus paca). Patches were characterized by patch area, resistance value or cost, distance from LCP, and distance from nearest neighbor across multiple forest density thresholds.

With the acceleration of urbanization in many parts of the world, transportation challenges such as traffic congestion, increasing carbon emissions, and the “first/last-mile” connectivity problems for commuter travel have arisen. Transport experts and policymakers have proposed shared transportation, such as dockless e-scooters and bike-sharing programs, to solve some of these urban transportation issues. In cities with high population densities, multimodal mobility hubs designed to integrate shared and public transportation can be implemented to achieve faster public connections and thus increase access to public transport on both access and egress sides. However, haphazard drop-offs of these dockless vehicles have led to complaints from community members and motivated the need for neighborhood-level parking areas (NLPAs). Simultaneously, concerns about the equitable distribution of transportation infrastructure have been growing and have led to the Biden Administration announcing the Justice40 Initiative which requires 40% of certain federal investments to benefit disadvantaged communities. To plan a system of NLPAs to address not only the transportation shortcomings while elevating these recent equity goals, this thesis develops a multi-objective optimal facility location model that maximizes coverage of both residential areas and transit stations while including a novel constraint to satisfy the requirements of Justice40. The model is applied to the City of Tempe, Arizona, and uses GIS data and spatial analyses of the existing public transportation stops, estimates of transit station boardings, population by census block, and locations of disadvantaged communities to optimize NLPA location. The model generates Pareto optimal tradeoff curves for different numbers of NLPAs to find the non-dominated solutions for the coverage of population nodes and boardings. The analysis solves the multi-objective model with and without the equity constraint, showing the effect of considering equity in developing a multimodal hub system, especially for disadvantaged communities. The proposed model can provide a decision support tool for transport and public authorities to plan future investments and facilitate multimodal transport.

Wildfire is a significant risk to property and people in the state of California. In 2018 alone, California's wildfire damages were estimated to be $148.5 Billion or 1.5% of the state's gross domestic product. Wildfire risks to property and people are at their highest at the intersection of flammable wildland vegetation and the built environment, a space called the Wildland Urban Interface or “WUI”. Existing methods for delineating the WUI, however, tend to be coarse in both spatial and temporal resolution, resulting in less precise estimates of WUI extent and change. This thesis uses high-resolution spatio-temporal data and classification methods to remap the WUI in California and to reassess the risk of residents and homes to wildfire. The findings from this analysis reveal that approximately $1.34 Trillion or 40% of the improved residential property value in the state falls within high wildfire risk areas. Likewise, areas classified as WUI account for over 10% of California's land area or a total of 43,205 square kilometers. While WUI areas cover a considerable portion of the state, the addition of a temporal element in this research shows WUI growth in California has slowed considerably over the past 10 years. The unique structure-level data integration strategy applied in this thesis provides a streamlined and expandable process for monitoring the WUI, enabling these new estimates of the hazard risk profiles of areas, structures, and people.

Public spaces have been central to studies focused on the relationship between economic inequalities, well-being, and environmental justice. However, an integrated examination of access to public spaces that is cognizant of the exchanges which inform environmental justice and the well-being of minoritized communities, is yet to be extensively studied. Such exchanges and the unideal community outcomes thereof are important to highlight in understanding access, given the historical challenges that have emanated from them to hamper the beneficial utility of public spaces in vulnerable contexts. This dissertation addresses this gap through a three-article format. Article 1 comprises a conceptual synthesis of two theoretical frameworks namely Lefebvre’s Tripartite Framework and Bishop’s Network Theory of Well-being that respectively conceptualize the exchanges in space production and the positive outcomes, which emerge from human and non-human engagements towards well-being. The main contribution of this article is the merging of two bodies of scholarship which had yet to intersect to inform investigations of access through the exchanges across technical (e.g., planners), social (i.e., communities) and physical (e.g., built spaces like parks) dimensions, and linkages to positive community outcomes. Article 2 entails an empirical examination of how communities and technical experts perceive of the linkages between access and community well-being, through exchanges across public space dimensions. Through a multiple embedded case study, 19 community leaders and 4 key technical informants in Maryvale were engaged in participatory mapping interviews. Responses to exchanges and outcomes thereof pertaining to the identified spaces, were deductively coded guided by the conceptual synthesis developed in article 1. Both community leaders and technical agents described access as emerging from perceptions of positive outcomes linked to public space exchanges. Article 3 sought to understand how design professionals (i.e., planners, building and landscape architects) who identify as ethnic minorities, perceive of their role in facilitating access to public spaces. Through interviews, 23 participants were engaged through a protocol guided by the conceptual synthesis developed in article 1. Responses were inductively coded. Participants described the role they play in exchanges, as focal to positive outcomes linked to access. Keywords: Public Spaces; Access; Environmental Justice; Community Well-being.

The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde River Watershed. This Story Map is intended for an audience of students in late middle school and early high school but can be a resource to teachers for a wider age range. The integration of interactive technology and virtual tools in educational practices is likely to continue past the immediate circumstances of the COVID-19 pandemic. The purpose of this Story Map is to showcase one of the many uses for geospatial web applications beyond the immediate realm of GIS.