Spatiotemporal data modeling for the analysis of the dynamic behavior of urban heat islands

Abstract

Urban Heat Island (UHI), widely acknowledged as an environmental phenomenon where temperatures in urban areas are higher than the surrounding rural areas, is a major problem in most of the metropolitan areas. Given the rapid urbanization, it is likely to be a serious problem in the growing mega cities due to the adverse effect on inhabitant health and increase of the energy consumption. To have more explicitly understanding of this phenomenon, previous research mainly focused on two aspects: - UHI intensity estimation and super-resolution reconstruction at a fixed time in­stant, where thermal satellite images with very fine spatial and / or temporal resolution covering a micro-scale of urban areas can rarely be obtained; and - causative factorial analysis by studying correlation between thermal images and the relevant factors (e.g. solar radiation, urban morphology, and anthropogenic heat). However, these studies are not capable to track the evolutionary process of the UHIs continuously in both time and space domains. Thus, objectives of this thesis are four-fold. The first objective is to conceptualize the UHI phenomenon as an object-based behavior. The second attempts to model dynamic behaviors of UHIs in three aspects (i.e., temperatures, areal extents, and locations). The third is to track the UHI spatial behaviors over time. The last objective is to evaluate the effectiveness of the model by computing with the near-surface thermal images. This study presents the concept of UHI and describes the previous research problems in continuously tracking dynamic behaviors of UHIs. The study also designs an object-oriented dynamic model to reconstruct the evolutionary process of UHIs. Each urban heat island is modeled as a spatiotemporal field-object with its own life-cycle, and dynamic behavior of a UHI is defined by a series of filiations. For instance, areal extent of UHI in two consecutive time instants can expand or contract. Further, the study proposes six hierarchical graphs to track continuous changes of the three properties. Finally, several patterns can be defined and revealed from the results. The developed model was implemented in an object-relational database and near-surface air temperature data collected from automatic weather stations on an hourly basis were applied into the model for the testing. Thematic and spatial behaviors of UHIs were analyzed, covering six months of time. Results suggest that the model can identify different behaviors and track complete life-cycles of UHIs effectively. This study has made several contributions and impacts for GIS modeling community. Interesting phenomena and evolutionary trends of UHIs in Guangzhou across different seasons are revealed. It also develops the theory of object-oriented data modeling systematically for tracking field geographical phenomena. In addition, this study provides some new approaches for the researchers to study different types of distributed spatial phenomena. The developed models can be used in urban planning to assist in mitigating the UHI phenomenon for building a sustainable city.