In the face of profound shock and change, individuals, organizations, and communities are seeking new ways to prepare for an uncertain future, their only certainty being that the present trajectory of change will intensify. Pandemics, wildfires, heat waves, hurricanes, flooding, social unrest, economic strife, and a rapidly changing climate system comprise a resounding wake up call: we must reinvent our institutions to think about and act with a resilient mindset. The purpose of the playbook is to support these efforts and build stronger, adaptive, and resilient communities.

The overarching aim of this dissertation is to evaluate Geodesign as a planning approach for American Indian communities in the American Southwest. There has been a call amongst indigenous planners for a planning approach that prioritizes indigenous and community values and traditions while incorporating Western planning techniques. Case studies from communities in the Navajo Nation and the Tohono O’odham Nation are used to evaluate Geodesign because they possess sovereign powers of self-government within their reservation boundaries and have historical and technical barriers that have limited land use planning efforts. This research aimed to increase the knowledge base of indigenous planning, participatory Geographic information systems (GIS), resiliency, and Geodesign in three ways. First, the research examines how Geodesign can incorporate indigenous values within a community-based land use plan. Results showed overwhelmingly that indigenous participants felt that the resulting plan reflected their traditions and values, that the community voice was heard, and that Geodesign would be a recommended planning approach for other indigenous communities. Second, the research examined the degree in which Geodesign could incorporate local knowledge in planning and build resiliency against natural hazards such as flooding. Participants identified local hazards, actively engaged in developing strategies to mitigate flood risk, and utilized spatial assessments to plan for a more flood resilient region. Finally, the research examined the role of the planner in conducting Geodesign planning efforts and how Geodesign can empower marginalized communities to engage in the planning process using Arnstein’s ladder as an evaluation tool. Results demonstrated that outside professional planners, scientists, and geospatial analysts needed to assume the role of a facilitator, decision making resource, and a capacity builder over traditional roles of being the plan maker. This research also showed that Geodesign came much closer to meeting American Indian community expectations for public participation in decision making than previous planning efforts. This research demonstrated that Geodesign planning approaches could be utilized by American Indian communities to assume control of the planning process according to local values, traditions, and culture while meeting rigorous Western planning standards.

Factors that explain human mobility and active transportation include built environment and infrastructure features, though few studies incorporate specific geographic detail into examinations of mobility. Little is understood, for example, about the specific paths people take in urban areas or the influence of neighborhoods on their activity. Detailed analysis of human activity has been limited by the sampling strategies employed by conventional data sources. New crowdsourced datasets, or data gathered from smartphone applications, present an opportunity to examine factors that influence human activity in ways that have not been possible before; they typically contain more detail and are gathered more frequently than conventional sources. Questions remain, however, about the utility and representativeness of crowdsourced data. The overarching aim of this dissertation research is to identify how crowdsourced data can be used to better understand human mobility. Bicycling activity is used as a case study to examine human mobility because smartphone apps aimed at collecting bicycle routes are readily available and bicycling is under studied in comparison to other modes. The research herein aimed to contribute to the knowledge base on crowdsourced data and human mobility in three ways. First, the research examines how conventional (e.g., counts, travel surveys) and crowdsourced data correspond in representing bicycling activity. Results identified where the data correspond and differ significantly, which has implications for using crowdsourced data for planning and policy decisions. Second, the research examined the factors that influence cycling activity generated by smartphone cycling apps. The best predictors of activity were median weekly rent, percentage of residential land, and the number of people using two or more modes to commute in an area. Finally, the third part of the dissertation seeks to understand the impact of bicycle lanes and bicycle ridership on residential housing prices. Results confirmed that bicycle lanes in the neighborhood of a home positively influence sale prices, though ridership was marginally related to house price. This research demonstrates that knowledge obtained through crowdsourced data informs us about smaller geographic areas and details on where people bicycle, who uses bicycles, and the impact of the built environment on bicycling activity.

Trees serve as a natural umbrella to mitigate insolation absorbed by features of the urban environment, especially building structures and pavements. For a desert community, trees are a particularly valuable asset because they contribute to energy conservation efforts, improve home values, allow for cost savings, and promote enhanced health and well-being. The main obstacle in creating a sustainable urban community in a desert city with trees is the scarceness and cost of irrigation water. Thus, strategically located and arranged desert trees with the fewest tree numbers possible potentially translate into significant energy, water and long-term cost savings as well as conservation, economic, and health benefits. The objective of this dissertation is to achieve this research goal with integrated methods from both theoretical and empirical perspectives.

This dissertation includes three main parts. The first part proposes a spatial optimization method to optimize the tree locations with the objective to maximize shade coverage on building facades and open structures and minimize shade coverage on building rooftops in a 3-dimensional environment. Second, an outdoor urban physical scale model with field measurement is presented to understand the cooling and locational benefits of tree shade. The third part implements a microclimate numerical simulation model to analyze how the specific tree locations and arrangements influence outdoor microclimates and improve human thermal comfort. These three parts of the dissertation attempt to fill the research gap of how to strategically locate trees at the building to neighborhood scale, and quantifying the impact of such arrangements.

Results highlight the significance of arranging residential shade trees across different geographical scales. In both the building and neighborhood scales, research results recommend that trees should be arranged in the central part of the building south front yard. More cooling benefits are provided to the building structures and outdoor microclimates with a cluster tree arrangement without canopy overlap; however, if residents are interested in creating a better outdoor thermal environment, open space between trees is needed to enhance the wind environment for better human thermal comfort. Considering the rapid urbanization process, limited water resources supply, and the severe heat stress in the urban areas, judicious design and planning of trees is of increasing importance for improving the life quality and sustaining the urban environment.

In light of climate change and urban sustainability concerns, researchers have been studying how residential landscape vegetation affect household water consumption and heat mitigation. Previous studies have analyzed the correlations among residential landscape practices, household water consumption, and urban heating at aggregate spatial scales to understand complex landscape decision tradeoffs in an urban environment. This research builds upon those studies by using parcel-level variables to explore the implications of vegetation quantity and height on water consumption and summertime surface temperatures in a set of single-family residential homes in Tempe, Arizona. QuickBird and LiDAR vegetation imagery (0.600646m/pixel), MASTER temperature data (approximately 7m/pixel), and household water billing data were analyzed. Findings provide new insights into the distinct variable, vegetation height, thereby contributing to past landscape studies at the parcel-level. We hypothesized that vegetation of different heights significantly impact water demand and summer daytime and nighttime surface temperatures among residential homes. More specifically, we investigated two hypotheses: 1) vegetation greater than 1.5 m in height will decrease daytime surface temperature more than grass coverage, and 2) grass cover will increase household water consumption more than other vegetation classes, particularly vegetation height. Bivariate and stepwise linear regressions were run to determine the predictive capacity of vegetation on surface temperature and on water consumption. Trees of 1.5m-10m height and trees of 5m-10m height lowered daytime surface temperatures. Nighttime surface temperatures were increased by trees of 5m-10m height and decreased by grass. Houses that experienced higher daytime surface temperatures consumed less water than houses with lower daytime surface temperatures, but water consumption was not directly related to vegetation cover or height. Implications of this study support the practical application of tree canopy (vegetation of 5m-10m height) to mitigate extreme surface temperatures. The trade-offs between water and vegetation classes are not yet clear because vegetation classes cannot singularly predict household water consumption.

Citizen Science programs create a bi-directional flow of knowledge between scientists and citizen volunteers; this flow democratizes science in order to create an informed public (Bonney et al. 2014; Brown, Kelly, and Whitall 2014). This democratization is a fundamental part of creating a science that can address today’s pressing environmental, economic, and social justice problems (Lubchenco 1998). While citizen science programs create an avenue for sharing knowledge between the public and scientists, the exact program details and dynamics leading to different outcomes have not been studied in detail. The current shortcomings in the literature fall into three categories. First, the concept of ‘volunteer’ is used as a catch-all without considering how different

demographics (e.g. young, old, wealthy, poor, differently abled, local inhabitants, and visitors) affect both volunteer and scientific outcomes of citizen science. The second shortcoming: there are no standards to assess the quality of citizen science datasets. The third shortcoming: the volunteer and scientific outcomes of these programs are not routinely, or strategically, measured, or integrated into policy and planning (Brossard, Lewenstein, and Bonney 2005). This research advances the understanding of tourist volunteers in citizen science by examining these three shortcomings through a case-study in Denali National Park and Preserve. This case study included the development of the Map of Life-Denali citizen science program is a “tourist-friendly” program. Volunteers of the program use the Map of Life- Denali mobile application to record wildlife observations in the park. Research conducted on this program shows that tourists can be successful citizen science volunteers, and when compared to resident volunteers produce similar data, and have positive volunteer outcomes. The development of a fitness for use assessment, called STAAq is also a part of this research. This assessment is shown to be an effective method for assessing citizen science data quality. Throughout the development and launch of the program, stakeholders (the Park Service, and Aramark) were consulted. The Map of Life-Denali program will be integrated into the park’s shuttle and tour bus systems as an educational tool, however, the scientific merits of the program are still disputed.

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics.