Map Library, Room 10.10, 10/F, The Jockey Club Tower, Centennial Campus, The University of Hong Kong
Urbanization and its environmental and ecological impacts in the Pearl River Delta
Dr ZHANG Hongsheng Institute of Space and Earth Information Science, The Chinese University of Hong Kong
Although urban areas occupy less than 1% of the world’s land surface, they contribute over 90% of the global economy. By 2014, already 50% of the world’s population was living in urban areas, and this figure is increasing. Pearl River Delta (PRD) has witnessed the world’s most dramatic urbanization process since 1980s. PRD is a special metropolitan area and includes three different urban planning and development policy bodies, more recently, known as Guangdong-Hong Kong-Macau Greater Bay Area. Our studies are mainly focused on two aspects. First, to understand the dynamics of urbanization in PRD, the urban impervious surfaces were analyzed. Urban impervious surfaces have been widely recognized as an important indicator of urban expansion and its related environmental issues, such as public health, urban heat islands and various environmental pollutants. The increase of urban impervious surfaces in PRD has led to a wide range of environmental and ecological issues. However, PRD is located in a subtropical climate zone characterized by rainy and cloudy weather throughout the year, and thus requires the most advanced remote sensing technology to overcome weather-related difficulties. We proposed a novel methodological framework using advanced machine learning models for accurate impervious surface estimation from optical and Synthetic Aperture Radar (SAR) data, to understand the dynamics of urbanization in the PRD region. Second, to evaluate the ecological impacts of urbanization in PRD, the mangrove forests in the Deep Bay in Hong Kong were investigated. Mangroves are ecosystems of considerable ecological, biological and socioeconomic significance. However, in Hong Kong, mangrove forests cover has rapidly decreased in the past few decades due to increasing agricultural exploitation and urbanization such as development of new highways and airport as well as associated construction. We employed advanced optical and SAR data for monitoring the mangrove forests and investigate the factors of its changes, to finally support the conservation and restoration of mangrove forests.
Spatial optimization for municipal solid waste collection in Singapore
Dr Kai CAO Department of Geography, National University of Singapore
Along with the rapid urbanization and population growth during past decades, the social and environmental impacts caused by municipal solid waste (MSW) have been paid increasing attention. How to collect and dispose the booming amounts of MSW turned to be a hot topic. Due to its advantages of cost-efficiency and environmental concerns, the incineration is replacing the direct landfilling for dealing with the MSW worldwide. Under the consideration of the limited number of incineration plants and the complicated situation of transportation in both spatial and temporal dimensions around different cities, how to effectively and efficiently allocate the incineration resources for different areas and how to find the optimal routes for waste collection turn to be critical and meaningful, especially in the highly populated cities, e.g., Singapore. In this research, the current MSW collection and disposal in Singapore is reviewed, especially the problematic allocation of incineration resources, and a spatial allocation model is proposed and successfully implemented accordingly. In addition, an ant colony optimization (ACO)-based multi-objective routing model coupled with min-max model and Dijkstra’s algorithm has also been proposed and successfully implemented to address the question of which route to take from these waste-generating points to the target incineration plant(s) considering travel time, accident probability (black spots), and population exposure in Singapore. Last but not the least, few limitations are also discussed, some of which would also be the future directions of this research.
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