CUHK electronic theses & dissertations collection

Contrasting the day-night variation in thermal landscape, the higher local variation and irregularity on urban surface temperature pattern during daytime was observed and identified by landscape metrics compared with those of nighttime pattern. The diversity and fragmentation metrics had revealed the influence of urban development on the overall urban landscape pattern. Along with urban development, daytime pattern of urban thermal landscape presented more fragmentation, less diversity and uneven texture distribution within daytime observations.During the process of worldwide urbanization along with high rise and high density housing development in large cities, urban warming has received growing concern among many environmental issues related to urban landscape change. Due to the complicated interplay between urban environment and local climate, it is far from certain about the urban effects on local warming. In this literature, a systematic monitoring and analysis of the spatial dependency and heterogeneity of urban thermal landscape at city scale remains inadequate. The goal of this doctoral research is to develop a research framework incorporating geospatial statistics, thermal infrared remote sensing and landscape ecology to study the urban effect on local surface thermal landscape regarding both the pattern and process.GWR analysis offered an in-depth investigation of local effect on surface temperature variation which had been proven to be spatially varying and influenced by local weather condition with local environmental setting quantified with the referred site specific environmental factors. The local dominant factor accounted for most to the site specific surface temperature variation which varied significantly in space and time and prevented a general delineation of the relative association among environmental factors to surface temperature disparities. The effective adaptive measures could be devised locally with reference to day-night needs in the identification of this feature.In summary, global regression analysis confirmed the relationship between environmental factors and surface temperature and gave a general overview of urban effect on local surface warming. The distinctive mechanism of dominating day-night surface warming was uncovered by regression analysis. Vegetation played the most important role which could be referred as surface cooling in average to local surface temperature variation as compared with other measures of local environment during both daytime and nighttime. Besides the dominant role of local solar radiation on surface warming, building square footage demonstrated the second important influence on local surface temperature elevation during daytime. During nighttime, population density played a dominant role on nighttime surface warming among different parameters, with the second important contribution of nighttime surface warming coming from road density. While elevation and distance from coast demonstrated obvious cooling effect on surface temperature within most nighttime models.Located in a subtropical region, Hong Kong's development with high rise and high density housing made it a suitable site for studying urban effect on local warming. This research chose Hong Kong as the case study which hopes to enrich our knowledge regarding urban local thermal performance and add to our understanding of urban microclimate in hot-humid weather area.Xue, Yucai.Adviser: Tung Fung.Source: Dissertation Abstracts International, Volume: 71-01, Section: B, page: 0185.Thesis submitted in: September 2008.Thesis (Ph.D.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (leaves 201-228).Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.Abstracts in English and Chinese