Remote sensing has demonstrated to be an instrumental tool in monitoring land changes as a result of anthropogenic change or natural disasters. Most disaster studies have focused on large-scale events with few analyzing small-scale disasters such as tornadoes. These studies have only provided a damage assessment perspective with the continued need to assess reconstruction. This study attempts to fill that void by examining recovery from the 1999 Moore, Oklahoma Tornado utilizing Landsat TM and ETM+ imagery. Recovery was assessed for 2000, 2001 and 2002 using spectral enhancements (vegetative and urban indices and a combination of the two), a recovery index and different statistical thresholds. Classification accuracy assessments were performed to determine the precision of recovery and select the best results. This analysis proved that medium resolution imagery could be used in conjunction with geospatial techniques to capture recovery. The new indices, Shortwave Infrared Index (SWIRI) and Coupled Vegetation and Urban Index (CVUI), developed for disaster management, were the most effective at discerning reconstruction using the 1.5 standard deviation threshold. Recovery rates for F-scale damages revealed that the most incredibly damaged areas associated with an F5 rating were the slowest to recover, while the lesser damaged areas associated with F1-F3 ratings were the quickest to rebuild. These findings were consistent for 2000, 2001 and 2002 also exposing that complete recovery was never attained in any of the F-scale damage zones by 2002. This study illustrates the significance the biophysical impact has on recovery as well as the effectiveness of using medium resolution imagery such as Landsat in future research.

Outdoor human comfort is determined for the remodelled downtown of Tempe, Arizona, USA, an acclaimed example of New Urbanist infill. The authors desired to know whether changes were accompanied by more comfortable conditions, especially in hot, dry summer months. The physiological equivalent temperature provided an assessment of year-round outdoor human comfort. Building compactness and tree shade that became part of the changes in the downtown provided more overall daytime human comfort than open nearby streets; however some downtown sites were less comfortable at night, but below 40°C, a threshold for human comfort in this desert environment.

Objectives: To provide novel quantification and advanced measurements of surface temperatures (Ts) in playgrounds, employing multiple scales of data, and provide insight into hot-hazard mitigation techniques and designs for improved environmental and public health.

Methods: We conduct an analysis of Ts in two Metro-Phoenix playgrounds at three scales: neighborhood (1 km resolution), microscale (6.8 m resolution), and touch-scale (1 cm resolution). Data were derived from two sources: airborne remote sensing (neighborhood and microscale) and in situ (playground site) infrared Ts (touch-scale). Metrics of surface-to-air temperature deltas (Ts–a) and scale offsets (errors) are introduced.

Results: Select in situ Ts in direct sunlight are shown to approach or surpass values likely to result in burns to children at touch-scales much finer than Ts resolved by airborne remote sensing. Scale offsets based on neighbourhood and microscale ground observations are 3.8 ◦C and 7.3 ◦C less than the Ts–a at the 1 cm touch-scale, respectively, and 6.6 ◦C and 10.1 ◦C lower than touch-scale playground equipment Ts, respectively. Hence, the coarser scales underestimate high Ts within playgrounds. Both natural (tree) and artificial (shade sail) shade types are associated with significant reductions in Ts.

Conclusions: A scale mismatch exists based on differing methods of urban Ts measurement. The sub-meter touch-scale is the spatial scale at which data must be collected and policies of urban landscape design and health must be executed in order to mitigate high Ts in high-contact environments such as playgrounds. Shade implementation is the most promising mitigation technique to reduce child burns, increase park usability, and mitigate urban heating.

Spatial uncertainty refers to unknown error and vagueness in geographic data. It is relevant to land change and urban growth modelers, soil and biome scientists, geological surveyors and others, who must assess thematic maps for similarity, or categorical agreement. In this paper I build upon prior map comparison research, testing the effectiveness of similarity measures on misregistered data. Though several methods compare uncertain thematic maps, few methods have been tested on misregistration. My objective is to test five map comparison methods for sensitivity to misregistration, including sub-pixel errors in both position and rotation. Methods included four fuzzy categorical models: fuzzy kappa's model, fuzzy inference, cell aggregation, and the epsilon band. The fifth method used conventional crisp classification. I applied these methods to a case study map and simulated data in two sets: a test set with misregistration error, and a control set with equivalent uniform random error. For all five methods, I used raw accuracy or the kappa statistic to measure similarity. Rough-set epsilon bands report the most similarity increase in test maps relative to control data. Conversely, the fuzzy inference model reports a decrease in test map similarity.

Urban climate conditions are the physical manifestation of formal and informal social forces of design, policy, and urban management. The urban design community (e.g. planners, architects, urban designers, landscape architects, engineers) impacts urban development through influential built projects and design discourse. Their decisions create urban landscapes that impact physiological and mental health for people that live in and around them. Therefore, to understand possible opportunities for decision-making to support healthier urban environments and communities, this dissertation examines the role of neighborhood design on the thermal environment and the effect the thermal environment has on mental health. In situ data collection and numerical modeling are used to assess current and proposed urban design configurations in the Edison Eastlake public housing community in central Phoenix for their efficacy in cooling the thermal environment. A distributed lagged non-linear model is used to investigate the relative risk of hospitalization for schizophrenia in Maricopa County based on atmospheric conditions. The dissertation incorporates both an assessment of design strategies for the cooling of the thermal environment and an analysis of the existing thermal environment’s relationship with mental health. By reframing the urban design of neighborhoods through the lens of urban climate, this research reinforces the importance of incorporating the community into the planning process and highlights some unintended outcomes of prioritizing the thermal environment in urban design.