This doctoral dissertation research aims to develop a comprehensive definition of urban open spaces and to determine the extent of environmental, social and economic impacts of open spaces on cities and the people living there. The approach I take to define urban open space is to apply fuzzy set theory to conceptualize the physical characteristics of open spaces. In addition, a 'W-green index' is developed to quantify the scope of greenness in urban open spaces. Finally, I characterize the environmental impact of open spaces' greenness on the surface temperature, explore the social benefits through observing recreation and relaxation, and identify the relationship between housing price and open space be creating a hedonic model on nearby housing to quantify the economic impact. Fuzzy open space mapping helps to investigate the landscape characteristics of existing-recognized open spaces as well as other areas that can serve as open spaces. Research findings indicated that two fuzzy open space values are effective to the variability in different land-use types and between arid and humid cities. W-Green index quantifies the greenness for various types of open spaces. Most parks in Tempe, Arizona are grass-dominant with higher W-Green index, while natural landscapes are shrub-dominant with lower index. W-Green index has the advantage to explain vegetation composition and structural characteristics in open spaces. The outputs of comprehensive analyses show that the different qualities and types of open spaces, including size, greenness, equipment (facility), and surrounding areas, have different patterns in the reduction of surface temperature and the number of physical activities. The variance in housing prices through the distance to park was, however, not clear in this research. This dissertation project provides better insight into how to describe, plan, and prioritize the functions and types of urban open spaces need for sustainable living. This project builds a comprehensive framework for analyzing urban open spaces in an arid city. This dissertation helps expand the view for urban environment and play a key role in establishing a strategy and finding decision-makings.
This dissertation includes two main parts. The first part proposes to employ the continuous, pixel-based landscape gradient models in comparison to the discrete, patch-based mosaic models and evaluates model efficiency in two empirical contexts: urban landscape pattern mapping and land cover dynamics monitoring. The second part formalizes a novel statistical model called spatially filtered ridge regression (SFRR) that ensures accurate and stable statistical estimation despite the existence of multicollinearity and the inherent spatial effect.
Results highlight the strong potential of local indicators of spatial dependence in landscape pattern mapping across various geographical scales. This is based on evidence from a sequence of exploratory comparative analyses and a time series study of land cover dynamics over Phoenix, AZ. The newly proposed SFRR method is capable of producing reliable estimates when analyzing statistical relationships involving geographic data and highly correlated predictor variables. An empirical application of the SFRR over Phoenix suggests that urban cooling can be achieved not only by altering the land cover abundance, but also by optimizing the spatial arrangements of urban land cover features. Considering the limited water supply, rapid urban expansion, and the continuously warming climate, judicious design and planning of urban land cover features is of increasing importance for conserving resources and enhancing quality of life.
United States have led to significant modifications in its environment at local and
regional scales. Both local and regional climate changes are expected to have massive
impacts on the hydrology of Colorado River Basin (CRB), thereby accentuating the need
of study of hydro-climatic impacts on water resource management in this region. This
thesis is devoted to understanding the impact of land use and land cover (LULC) changes
on the local and regional hydroclimate, with the goal to address urban planning issues
and provide guidance for sustainable development.
In this study, three densely populated urban areas, viz. Phoenix, Las Vegas and
Denver in the CRB are selected to capture the various dimensions of the impacts of land
use changes on the regional hydroclimate in the entire CRB. Weather Research and
Forecast (WRF) model, incorporating the latest urban modeling system, is adopted for
regional climate modeling. Two major types of urban LULC changes are studied in this
Thesis: (1) incorporation of urban trees with their radiative cooling effect, tested in
Phoenix metropolitan, and (2) projected urban expansion in 2100 obtained from
Integrated Climate and Land Use Scenarios (ICLUS) developed by the US
Environmental Protection Agency for all three cities.
The results demonstrated prominent nocturnal cooling effect of due to radiative
shading effect of the urban trees for Phoenix reducing urban surface and air temperature
by about 2~9 °C and 1~5 °C respectively and increasing relative humidity by 10~20%
during an mean diurnal cycle. The simulations of urban growth in CRB demonstratedii
nocturnal warming of about 0.36 °C, 1.07 °C, and 0.94 °C 2m-air temperature and
comparatively insignificant change in daytime temperature, with the thermal environment
of Denver being the most sensitive the urban growth. The urban hydroclimatic study
carried out in the thesis assists in identifying both context specific and generalizable
relationships, patterns among the cities, and is expected to facilitate urban planning and
management in local (cities) and regional scales.