In recent years environmental life-cycle assessments (LCA) have been increasingly used to support planning and development of sustainable infrastructure. This study demonstrates the application of LCA to estimate embedded energy use and greenhouse gas (GHG) emissions related to materials manufacturing and construction processes for low and high density single-family neighborhoods typically found in the Southwest. The LCA analysis presented in this study includes the assessment of more than 8,500 single family detached units, and 130 miles of related roadway infrastructure. The study estimates embedded and GHG emissions as a function of building size (1,500 - 3000 square feet), number of stories (1 or 2), and exterior wall material composition (stucco, brick, block, wood), roof material composition (clay tile, cement tile, asphalt shingles, built up), and as a function of roadway typology per mile (asphalt local residential roads, collectors, arterials). While a hybrid economic input-out life-cycle assessment is applied to estimate the energy and GHG emissions impacts of the residential units, the PaLATE tool is applied to determine the environmental effects of pavements and roads. The results indicate that low density single family neighborhoods are 2 - 2.5 X more energy and GHG intensive, per residential dwelling (unit) built, than high density residential neighborhoods. This relationship holds regardless of whether the functional unit is per acre or per capita. The results also indicate that a typical low density neighborhood (less than 2 dwellings per acre) requires 78 percent more energy and resource in roadway infrastructure per residential unit than a traditional small lot high density (more than 6 dwelling per acre). Also, this study shows that new master planned communities tend to be more energy intensive than traditional non master planned residential developments.

This study is an initial step in exploring how urban design typologies can help inform community asset research to broaden the definition of physical assets. Asset based community development research identifies specific types of physical assets such as streets, structures, housing or vacant lots. This research argues that a comprehensive look at physical assets is needed, taking into consideration urban typologies such as paths, landmarks, views and districts as well as the spatial relationships that influence their significance. Community asset literature and conditions specific to the Sunnyslope community in Phoenix, Arizona suggest that differences in ethnicity such as spatial segregation, and socio-economic status exist. However, the literature does not address how these differences in ethnicity might influence residents' perceptions of physical assets. This study explores the questions - How do perceptions of physical assets vary among women of different ethnicities? What, if any, are the reasons behind these ethnic differences in perception? The research applied a survey instrument with open-ended and close-ended questions, and a map to mark frequently used routes. Assets identified by recoding open-ended responses were statistically analyzed for frequencies. The most frequently mentioned assets were analyzed by GIS for spatial relationships. Women of White and Latino ethnicities frequently chose individual buildings and locations as physical assets over paths, views, districts and landmarks. White women identified urban typologies as physical assets. In contrast, Latino women identified no significant urban typologies as assets. The inclusion of urban typologies confirmed and expanded upon physical assets previously identified by other asset-based studies on the community of Sunnyslope. Notable differences in ethnicity were found in the perception of physical assets of economic significance, assets for use and assets of visual appeal. Besides ethnicity, age and proximity to assets also influenced asset perception of White and Latino women. Community organizations need to take into consideration the ethnic differences in perception of physical assets, in the context of culture, spatial segregation and differing family structures. The inclusion of urban typologies helped highlight the differences in ethnicities for physical assets of visual appeal, and the use of leisure and recreation facilities.

Slum development and growth is quite popular in developing countries. Many studies have been done on what social and economic factors are the drivers in establishment of informal settlements at a single cross-section of time, however limited work has been done in studying their spatial growth patterns over time. This study attempts to study a sample of 30 informal settlements that exist in the National Capital Territory of India over a period of 40 years and identify relationships between the spatial growth rates and relevant factors identified in previous socio-economic studies of slums using advanced statistical methods. One of the key contributions of this paper is indicating the usefulness of satellite imagery or remote sensing data in spatial-longitudinal studies. This research utilizes readily available LANDSAT images to recognize the decadal spatial growth from 1970 to 2000, and also in extension, calculate the BI (transformed NDVI) as a proxy for the intensity of development for the settlements. A series of regression models were run after processing the data, and the levels of significance were then studied and compared to see which relationships indicated the highest levels of significance. It was observed that the change in BI had a higher strength of relationships with the change in independent variables than the settlement area growth. Also, logarithmic and cubic models showed the highest R-Square values than any other tested models.